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Mehmet Celenk

Professor
Electrical Engineering and Computer Science
STKR 343
celenk@ohio.edu
Phone: 740.593.1581


Research Interests: Electrical Engineering & Computer Science, Digital Image Processing, Computer Vision and Pattern Recognition, Multiprocessor Systems and Distributed Computing, Multimedia and Internet Communications, Parallel Processing and Information Technology, Computer Architecture and Embedded Digital System Design, Video Teleconferencing

Journal Article, Academic Journal (32)

  • Celenk, M., Altun, M. Road Scene Content Analysis for Driver Assistance and Autonomous Driving. IEEE Transactions on Intelligent Transportation Systems.
  • Celenk, M., Kaufman, J. Assessment of Spatial-Spectral Feature-Level Fusion for Hyperspectral Target Detection. Piscataway, NJ: IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, Special Issue on “Hyperspectral remote sensing.
  • Celenk, M., Altun, M. Road Scene Content Analysis for Driver Assistance and Autonomous Driving. Piscataway, NJ: IEEE Transactions on Intelligent Transportation Systems.
  • Celenk, M., Kaufman, J., Eismann, M. Assessment of Spatial-Spectral Feature-Level Fusion for Hyperspectral Target Detection. IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, Special Issue on Hyperspectral remote sensing.
  • Celenk, M. A Novel Matching of MR Images Using Gabor Wavelets. 3. J. of IETE (The Institution of Electronics and Telecomm. Engineers) Technical Review, Vol.30, Issue 3; 30.
  • Celenk, M., Fu, Q. Spatio-Temporal Video Motion Detection Using Marked-Watershed and Morphological Operations . Journal of Communication and Computer.
  • Altun, M., Celenk, M. Smoke Detection via Video Surveillance and Optical Flow Divergence. Journal of Computer Science, Technology and Application.
  • Celenk, M., Riley, B. Robust lane detection in shadows and low illumination conditions using local gradient features. Hainan Island : Open Journal of Applied Sciences ; 7. http://www.scirp.org/journal/ojapps/.
  • Celenk, M., Akinlar1, M., Kurulay, M., Secer, A. Curvature-driven diffusion-based mathematical image registration models. 193. Advances in Difference Equations (Springer Open Journal).
  • Akinlar, M., Kurulay, M., Secer, A., Celenk, M. A Computational Method Using Multiresolution For Volumetric Data Integration. Boundary Value Problems (SpringerOpen Journal); 115.
  • Celenk, M., Altun, M. Image Fusion Based Video Content Enhancement for Surveillance and Tracking. 2. ICGST Journal of Graphics, Vision and Image Processing (Open Access); 12: 9-14.
  • Akinlar, M., Celenk, M. Quality Assessment for an Image Registration Method. 30. Int. J. Contemp. Math. Sciences; 6: 1483-1490. http://www.m-hikari.com/ijcms-2011/29.../akinlarIJCMS29-32-2011.pdf.
  • Celenk, M., Conley, T., Willis, J., Graham, J. Predictive network anomaly detection and visualization. 2. Piscataway, NJ: IEEE Transactions on Information Forensic and Security ; 5: 288-299. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5411760&tag=1.
  • Celenk, M., Farrell, M., Eren, H., Kumar, K., Singh, G., Lozanoff, S. Upper airway detection and visualization in cone beam images. 2. Amsterdam: Journal of X-Ray Science and Technology; 18: 121-135. http://iospress.metapress.com/content/y4103643l0254589/.
  • Celenk, M., Farrel, M., Eren, H., Kumar, K., Singh, G., Lozanoff, S. Upper airway detection and visualization in cone beam images. J. X-Ray Science & Technology.
  • Celenk, M., Conley, T., Willis, J., Graham, J. Predictive network anomaly detection and visualization. IEEE Trans. on Information Forensic & Security.
  • Zhou, Q., Ma, L., Celenk, M., Chelberg, D. Content-based image retrieval based on ROI detection and relevance feedback. Journal of Multimedia Tools and Applications: Special Issue on Multimedia Retrieval Algoritmics; 27: 251-281.
  • Celenk, M., Zhou, Q., Vetnes, V., Godavari, R. Saliency field map construction for ROI-based color image querying. 3. Journal of Electronic Imaging; 4: 033012-1 ~ 033012-9.
  • Celenk, M., Zhou, Q., Godavari, R., Vetnes, V. Shape representation for color image querying. 2. Electronic Imaging: SPIE’s Int. Tech. Group Newsletter; 12: 6 – 8.
  • Shao, Y., Celenk, M. Higher-order spectra (HOS) invariants for shape recognition. 11. Pattern Recognition Journal; 34: 2097-2113.
  • Celenk, M. Computation of vision operators in hypercube processors. 4. Computers & Electrical Engineering Journal; 21: 243-261.
  • Celenk, M., Wang, Y. Distributed computation in local area networks of workstations. Journal of Parallel Algorithms and Applications; 5: 79-106.
  • Celenk, M. Analysis of color images of natural scenes. 4. Journal of Electronic Imaging; 4: 386-396.
  • Celenk, M. Speedup analysis of hypercube array processor for machine vision applications. Journal of Parallel Algorithms and Applications; 1: 221-242.
  • Celenk, M. Colour image segmentation by clustering. 5. IEE Proceedings-E; 138: 368-376.
  • Celenk, M., Datari, S. Hypercube concurrent processor implementation of a position invariant object classifier. 2. IEE Proceedings-E; 138: 73-78.
  • Celenk, M., Lim, C. Parallel implementation of low-level vision operators on a hypercube machine. 3. Optical Engineering; 30: 275-284.
  • Celenk, M. A color clustering technique for image segmentation. Journal of Computer Vision Graphics, and Image Processing; 52: 145-170.
  • Celenk, M., Reza, H. Fast detection, location, and trajectory tracing of moving targets. 5. Pakistan Journal of Scientific and Industrial Research; 32: 291-293.
  • Celenk, M. An adaptive machine learning algorithm for color image analysis and processing. 3/4. J.Robotics and Computer-Integrated Manufacturing; 4: 403-412.
  • Celenk, M., Erbug, H. A survey on fiber optic systems. 1. Ankara, Turkey: Communications Journal, Signal School; 19-34.
  • Celenk, M., Coruh, E. Effects of nuclear explosions on communication systems. 1. Ankara, Turkey: Communications Journal, Signal School; 35-43.

Conference Proceeding (179)

  • Celenk, M., Yakut, O., Eren, H., Kaya, M., Oksuztepe, E., Polat, M., Omac, Z., Kurum, H. 'Estimation of Confidence Regions and Severity of Undefined Faults in Driving using Synthetic Disturbance Signals. Florence, Italy: 2014 IEEE International Electric Vehicle Conference (IEVC 2014).
  • Celenk, M., Grudath, N., Riley, B. Machine Learning Identification of Diabetic Retinopathy from Fundus Images. Philadelphia, Pennsylvania: 2014 IEEE Signal Processing in Medicine and Biology Symposium (SPMB 14).
  • Gurudath, N., Celenk, M., Riley, H. Machine Learning Identification of Diabetic Retinopathy from Fundus Images. IEEE Xplore.
  • Celenk, M., Karaduman, O., Eren, H., Kurum, H. Regional Risk Estimation for Drivers Cutting Intelligent Graph with Intra Cells Enabling Risk Transfer for Street Players. Vienna, Austria: The 3rd International Conference on Connected Vehicles & Expo (ICCV 2014).
  • Celenk, M., Dhinagar, N. Analysis of Regularity in Skin Pigmentation and Vascularity by an Optimized Feature Space for Early Cancer Classification. Dalian, China: 2014 7th International Conference on BioMedical Engineering and Informatics (BMEI 2014).
  • Celenk, M., Karaduman, O., Eren, H., Kurum, H. Graph-Cut Based Regional Risk Estimation for Traffic Scene. Qingdao, China: 17th International IEEE Conference on Intelligent Transportation Systems (ITS’2014).
  • Celenk, M., Kaufman, J., Weinheimer, J. Spatial-spectral feature extraction on hyperspectral imagery. Lausanne, Switzerland: WHISPER 2014, 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing.
  • Celenk, M., Kaufman, J. Bobcat 2013: A hyperspectral data collection supporting the development of spatial-spectral algorithms. Baltimore, MD: SPIE DSS 2014 (Defense, Security, and Sensing).
  • Celenk, M., Dhinagar, N. Performance Assessment of the Use of the RGB and LAB Color Spaces for Non-invasive Skin Cancer Classification. Las Vegas, NV: 29th Int. Conf. on Computer and Their Applications (CATA-2014).
  • Celenk, M., Eren, H. Bayesian Learning of Driver Head Motion via Interframe Optical Flow Clustering. Hangzhou, China: CISP-BMEI 2013 Conf.
  • Celenk, M., Aytac Korkmaz, S., Eren, H., Poyraz, M. Cancer Detection in Mammograms Calculating Feature Weights via Kullback-Leibler Measure. Hangzhou, China: The 2013 6th Int. Congress on Image and Signal Processing (CISP 2013) and the 2013 6th International Conference on BioMedical Engineering and Informatics (BMEI 2013).
  • Celenk, M., Yakut, O., Eren, H., Kaya, M., Oksuztepe, E., Polat, M., Omac, Z., Bekler, D., Kurum, H. Dynamic Risk Assesment for Driver Response in Passing over Obstacles. Hangzhou, China: CISP-BMEI 2013 Conf.
  • Celenk, M., Karaduman, O., Eren, H., Kurum, H. Similar Association Set Based Attribute Selection Algorithm for Road Profile Detection. Hangzhou, China: CISP-BMEI 2013 Conf.
  • Celenk, M., Karaduman, O., Eren, H., Kurum, H. An Effective Variable Selection Algorithm for Aggressive/Calm Driving Detection via CAN Bus. Las Vegas, Nevada: IEEE ICCVE 2013.
  • Celenk, M., Yakut, O., Eren, H., Kaya, M., Oksuztepe, E., Polat, M., Omac, Z., Bekler, D., Kurum, H. Dynamic Risk Modeling for Safe Car Parking in Climbing over Urban Curbs. Las Vegas, Nevada: IEEE ICCVE (Int. Conf. on Connected Vehicle) 2013.
  • Celenk, M., Yakut, O., Eren, H., Kaya, M., Oksuztepe, E., Polat, M., Kurum, H., Omac, Z., Yilmaz, A. Fault Severity Classification and Confidence Region Prediction for Driving Assistance Systems. The Hague, The Netherlands: 16th Int. IEEE Conf. on Intelligent Transport System (ITSC 2013).
  • Celenk, M., Fu, Q. Marked Watershed and Image Morphology Based Moving Detection and Performance Analysis. Triesta, Italy: IEEE 8th Int. Symp. on Image and Signal Processing and Analysis (ISPA 2013).
  • Celenk, M., Khalili, F., Akinlar, M. Medical image compression using quad-tree fractials and segmentation. Las Vegas, Nevada: Proc. of Int. Conf. on Pattern Recognition (IPCV2013).
  • Celenk, M., Altun, M. Smoke detection in video surveillance using optical flow and Green’s theorem. Las Vegas, Nevada: Proc. of Int. Conf. on Pattern Recognition (IPCV2013).
  • Celenk, M., Fu, Q. Video object segmentation using spatio-temporal information and marked-watershed operation. Las Vegas, Nevada: Proc. of Int. Conf. on Pattern Recognition (IPCV2013).
  • Celenk, M., Karaduman, O., Eren, H., Kurum, H. Interactive risky behavior model for 3-car overtaken scenario using joint Bayesian network. Gold Coast, Australia: IEEE Intelligent Vehicle (IEEE IV 2013) Symposium.
  • Celenk, M. Robust Lane Detection in Shadows and Low Illumination Condition Using Local Gradient Features. Hainan Island, China: Proc. Conference on Image Processing, CIP 2013.
  • Celenk, M. Robust Lane Detection in Shadows and Low Illumination Condition Using Local Gradient Features. Hainan Island, China: Proc. Conference on Image Processing, CIP 2013.
  • Celenk, M., Dhinagar, N. Ultrasound Medical Image Enhancement and Segmentation Using Adaptive Homomorphic Filtering and Histogram Thresholding. IEEE-EMBS Conference on Biomedical Engineering, Langkawi, Malaysia.
  • Celenk, M., Akinlar, M., Kurulay, M., Secer, A. Curvature Drıven Diffusion Based Medical Image Registration Methods. First International Conference on Analysis and Applied Mathematics (ICAAM 2012),Istanbul, Turkey.
  • Celenk, M., Dhinagar, N. Cancerous Lesion Detection from Nevoscope Skin Surface Images via Parametric Color Clustering. Chinese Conference on Pattern Recognition (CCPR 2012), Beijing, China.
  • Celenk, M., Karaduman, O., Eren, H., Kurum, H. Approaching Car Detection Via Clustering of Vertical-Horizontal Line Scanning Optical Edge Flow. 15th International IEEE Annual Conference on Intelligent Transportation Systems (IEEE- ITS 2012), Anchorage, Alaska.
  • Altun, M., Celenk, M. Multi-Sensory Image Data Fusion for Video and Occlusion Surveillance. ICGST-ACM Int. Conf. on Computer Science and Engineering ; http://icgst.com/conferences/conference.aspx?confid=55.
  • Dihinagar, N., Celenk, M. Power spectra based classification of cancerous Nevoscope skin images. 2011 IEEE Conf. on Computer Applications & Industrial Electronics; http://www.isiea.org/2011/.
  • Dihinagar, N., Celenk, M. Non-invasive detection and classification of skin cancer from visual and cross-sectional images (INVITED). 4th Int. Symposium on Applied Sciences in Biomedical and Communications Technologies; http://www.isabelconference.com/.
  • Dihinagar, N., Celenk, M., Akinlar, M. Noninvasive screening and discrimination of skin images for early melanoma detection. The 5th IEEE iCBBE 2011; http://www.icbbe.org/2011/.
  • Celenk, M., Altun, M. X-ray and fluorescent molecular tomography image fusion. Chengdu: The 4th IEEE Int. Conf. Bioinformatics and Biomedical Engineering (iCBBE 2010) ; http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=5513048.
  • Luo, Y., Celenk, M. Fast binary partition tree based variable-size block-matching for video coding. Cairo, Egypt: Proc. IEEE ICIP.
  • Singh, S., Celenk, M. Highly directional and selective three dimensional adaptive IIR filter. Cancun, Mexico: IEEE Midwest Symp. on Circuits and Systems.
  • Celenk, M., Eren, H., Poyraz, M. Prediction of driver head movement via Bayesian learning and ARMA modeling. Xian, China: Proc. IEEE Intell. Vehic. Symp.
  • Celenk, M., Farrel, M., Eren, H., Kumar, K., Singh, G., Lozanoff, S. Upper airway detection in cone beam images. Beijing, China: The 3rd Int. Conf. Bioinformatics and Biomedical Engineering (iCBBE).
  • Graham, J., Celenk, M., Willis, J., Conley, T., Eren, H. Multiple vehicle tracking using Gabor filter bank predictor. Lisbon, Portugal: Proc. Int. Conf. on Computer Vision Theory and Applications (VISAPP).
  • Celenk, M., Conley, T., Graham, J., Willis, J. Anomaly detection and visualization using Fisher linear discriminant clustering of network entropy. Univ. of East London, UK: Proc. Third IEEE Int. Conf. on Digital Information Management.
  • Celenk, M., Conley, T., Graham, J., Willis, J. Anomaly prediction in network traffic using adaptive Wiener filtering and ARMA modeling. Singapore: Proc. The IEEE Int. Conf. on Systems, Man, and Cybernetics 2008.
  • Luo, Y., Celenk, M. Kalman filtering based motion estimation for video coding with adaptive block partitioning. Washington, D.C.: Proc. 2008 IEEE Workshop on Signal Processing Systems.
  • Luo, Y., Celenk, M. Motion estimation for video compression using Kalman filtering with adaptive adjustment. Xian, China: Proc. The 5th Int. Conf. on Visual Information Engineering.
  • Singh, S., Celenk, M. Shape adaptive three dimensional cone filter bank. Knoxville, TN: Proc. The 51st IEEE Annual Midwest Symp. on Circuits and Syst.
  • Luo, Y., Celenk, M. Spatio-temporal correlation based adaptive rood search for block- matching motion estimation. Kailua-Kona, Hawaii: Proc. The 10th IASTED Int. Conf. on Signal and Image Processing.
  • Luo, Y., Celenk, M. An efficient adaptive rood pattern search algorithm for fast block motion estimation. Bilbao, Spain: Proc. 4th Int. Symp. on Image/Video Com.
  • Luo, Y., Celenk, M. A hybrid block-matching approach to motion estimation with adaptive search area. Bratislava, Slovakia: Proc. 15th Int. Conf. on Syst., Signals, and Image Proc.; 85-88.
  • Luo, Y., Celenk, M. A new adaptive Kalman filtering method for block-based motion estimation. Bratislava, Slovakia: Proc. 15th Int. Conf. on Syst., Signals, and Image Proc.; 89-92.
  • Kaufman, J., Celenk, M., Vongsy, K. A 2DPCA-based method for automatic selection of hyper-spectral image bands for color visualization. Orlando, FL: SPIE Defense + Security 2008, Conf. on Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV, Proc. SPIE; 6966.
  • Celenk, M., Graham, J., Singh, S. Traffic surveillance using Gabor filter bank and Kalman predictor. Funchal, Madeira, Portugal: 3rd Int. Conf. Computer Vision Theory and Applications (VISAPP 2008).
  • Celenk, M., Venable, D., Smearcheck, M., Graham, J. Change detection and object tracking in IR surveillance video. Shanghai Jiaotong Univ., China: The Third Int. Conf. on Signal-Image Technology & Internet-Based Systems (SITIS’ 2007).
  • Celenk, M., Graham, J., Venable, D., Smearcheck, M. A Kalman filtering approach to 3D IR scene prediction using single-camera range video. San Antonio, TX: IEEE Int. Conf. on Image Proc. (ICIP’07).
  • Celenk, M., Graham, J., Cheng, K. Non-linear IR scene prediction for range video surveillance. Minneapolis, MN: 4th Joint IEEE Int. Workshop on Object Tacking and Classification in and Beyond the Visible Spectrum (OTCBVS’07).
  • Macenko, M., Luo, R., Celenk, M., Ma, L., Zhou, Q. Lesion detection using Gabor- based saliency field mapping. San Diego, CA: Medical Imaging 2007, Proc. SPIE; 6512.
  • Kaufman, J., Celenk, M. Digital video watermarking using SVD and 2DPCA. Atlanta, GA: Proc. IEEE ICIP.
  • Zhou, Q., Celenk, M., Ma, L., Chelberg, D. Object detection and recognition via deformable illumination and deformable shape. Atlanta, GA: Proc. IEEE Int. Conf. Image Processing (ICIP).
  • Macenko, M., Celenk, M., Ma, L. Lesion detection using morphological watershed segmentation and model-based inverse filtering. Hong Kong: Proc. 18th Int. Conf. on Pattern Recognition (ICPR).
  • Luo, Y., Celenk, M., Bejai, P. Discrimination of malignant lymphomas and leukemia using Radon-transform based-higher order spectra. San Diego, CA: Proc. SPIE Vol. 6144, Medical Imaging 2006.
  • Celenk, M., Aljarrah, I. Internal shape-deformation invariant 3D surface matching using 2D principal component analysis. San Jose, CA: Proc. SPIE Vol. 6056, Electronic Imaging: 3-D Image Capture & Applications VII.
  • Luo, Y., Celenk, M. Higher-order spectra analysis of silhouette for gait recognition. Cairo, Egypt: Proc. Int. Conf. on Graphics, Vision and Image Proc.
  • Ma, L., Chelberg, D., Celenk, M. Spatio-temporal modeling of facial expressions using Gabor wavelets and hierarchical hidden Markov models. Genoa, Italy: Proc. IEEE Int. Conf. on Image Processing (ICIP).
  • Luo, Y., Celenk, M. Topographic modeling of cellular images. Shanghai, China: Proc. 27th Int. Conf. IEEE Engineering in Medicine and Biology Society.
  • Celenk, M., Brown, M., Luo, Y., Kaufman, J., Ma, L., Zhou, Q. Human identification using correlation metrics of iris images. San Jose, CA: Storage and Retrieval Methods and Applications for Multimedia 2005, Proc. SPIE; 5682: 53-63.
  • Ma, L., Zhou, Q., Celenk, M., Chelberg, D. Facial event mining using coupled hidden Markov models. Singapore: IEEE Int. Conf. Image Processing.
  • Ma, L., Zhou, Q., Chelberg, D., Celenk, M. Shape-based image retrieval with relevance feedback. Taipei, Taiwan: IEEE Int. Conf. Multimedia and Expo.
  • Celenk, M., Yang, L., Kamalakar, G., Bleyle, D., Sunkara, S., Wang, Y., Prudich, P., Huang, Y., Zhou, Q. Tumor detection in vivo NIRF images. San Diego, CA: Medical Imaging 2004, Proc. SPIE; 5370: 2122-2129.
  • Celenk, M., Zhou, Q., Wang, P. Content-based video indexing and retrieval using Radon transform and pattern matching. San Jose, CA: Storage and Retrieval Methods and Applications for Multimedia 2004, Proc. SPIE; 5307: 460-471.
  • Zhou, Q., Ma, L., Chelberg, D., Celenk, M. Color and texture priors in active contours for model-based image segmentation. Rome, Italy: Proc. 3rd Int. Symp. on Image and Signal Processing and Analysis (ISPA 2003); 690-695.
  • Zhou, Q., Ma, L., Celenk, M., Chelberg, D. Natural scene synthesis using multiple eigenspaces. Barcelona, Spain: Proc. 2003 IEEE Int. Conf. on Image Processing (ICIP-2003).
  • Celenk, M., Song, Y., Ma, L., Zhou, M. Shape classification of malignant lymphomas and lukemia by morphological watersheds and ARMA modeling. San Diego, CA: Medical Imaging 2003, Proc. SPIE; 5032: 265-276.
  • Celenk, M., Zhou, Q., Vetnes, V., Godavari, R. Adaptive shape transform for color image querying. 21-23. Santa Clara, CA: Image Processing: Algorithms and Systems II, Proc. SPIE; 5014: 86-98.
  • Celenk, M., Al-Jarrah, I. Color face recognition by autoregressive moving averaging. Poitiers, France: CGIV’2002, First European Conf. on Color in Graphics, Imaging, and Vision.
  • Celenk, M., Zhou, Q., Chelberg, D. Equal-intensity map texture modeling for natural scene segmentation. Santa Fe, New Mexico: Proc. IEEE Southwest Symp. on Image Analysis and Interpretation; 219-223.
  • Celenk, M., Al-Jarrah, I. Multiresolution ARMA modeling of facial color images. San Jose, CA: Proc. SPIE Vol.467, Iimage Processing: Algorithms and Systems.
  • Celenk, M., Godavari, R., Vetnes, V. Web server for priority ordered multimedia services. Beijing, China: APOC 2001, Asia-Pacific Optical and Wireless Conference and Exhibition; 4584: 142-153.
  • Kiryukhin, G., Celenk, M. Implementation of 2D-DCT on XC4000 series FPGA using DFT-based DSFG and DA architectures. Thessaloniki, Greece: IEEE Int. Conf. Image Processing.
  • Godavari, R., Celenk, M. Synchronization of conference presentation sequence using delay equalization approach. Denver, CO: ITCom 2001, Con. Multimedia Systems & Appl. IV; SPIE Vol.4518: 128-138.
  • Zhou, Y., Celenk, M. Color scene classification by Zernike moment invariants. Orlando, FL: Proc. SPIE Vol.4388, Visual Information Processing X; 46-55.
  • Godavari, R., Eati, K., Celenk, M. Hierarchical teleconferencing on the Internet. Athens, OH: 33rd Southeastern Symp. System Theory; 319-323.
  • Zhou, Q., Celenk, M. Color-invariant shape moments for object recognition. San Jose, CA: Proc. SPIE Vol.4304, Nonlinear Image Proc. & Pat. Anal. XII; 7-17.
  • Celenk, M., Al-Jarrah, M. Internet traffic characterization for real-time collaborative applications. Boston, MA: Proc. SPIE, Internet Quality and Performance and Control of Network Systems; 4211: 47-58.
  • Celenk, M., Bobik, S. Edge-suppressed color image indexing and retrieval. St-Etienne, France: First Int. Conf. Color in Graphics and Image Proc.; 250-255.
  • Celenk, M., Chang, I. Connectionist model of three-link pendulum for NN-simulation. Orlando, FL: Proc. SPIE, Applications and Science of Computational Intelligence III; 4055: 28-35.
  • Celenk, M., Al-Jarrah, M. Effective network bandwidth utilization for video-teleconferencing. Tallahassee, FL: 32nd Southeastern Symp. System Theory; 194-198.
  • Celenk, M., Chang, I. Karhunen-Loeve transformation for optimal color feature generation. Portland, Oregon: IS&T’s PICS Conference; 307-311.
  • Celenk, M., Uijt de Haag, M. Wavelet-based edge enhancement for color images. Las Vegas, NV: IS&T’s Eleventh Int. Symp. Photo-finishing Technologies; 5-9.
  • Celenk, M., Uijt de Haag, M. Edge-suppressed color clustering for image thresholding. San Jose, CA: Proc. SPIE, Nonlinear Image Processing XI; 3961: 116-125.
  • Shao, Y., Celenk, M. Relative entropy-based feature matching for image retrieval. San Jose, CA: Proc. SPIE, Internet Imaging; 3964: 70-78.
  • Shao, Y., Celenk, M. Radon transform, bispectra, and principal component analyses for RTS invariant image retrieval. Boston, MA: Proc. SPIE, Multimedia Storage and Archiving Systems IV; 3846: 236-243.
  • Celenk, M., Uijt de Haag, M. Multivariate Gaussian modeling of object colors for image analysis. Savannah, GA: IS&T’s Image Processing, Image Quality, Image Capture Systems Conference; 364-366.
  • Celenk, M. Efficient multimedia image retrieval system. Orlando, FL: Proc. SPIE, Visual Information Processing VIII; 3716: 92-99.
  • Celenk, M., Uijt de Haag, M. Automatic boundary detection in color images. Auburn, AL: 31st Southeastern Symp. System Theory; 75-79.
  • Celenk, M., Al-Jarrah, M., Eati, K. Intelligent network manager for distributed multimedia conferencing. Auburn, AL: 31st Southeastern Symp. System Theory; 65-69.
  • Celenk, M., Shao, Y. On the use of bispectrum and Mellin transform for translation and scaling invariant feature extraction for one-dimensional pattern. Auburn, AL: 31st Southeastern Symp. System Theory; 80-83.
  • Celenk, M., Shao, Y. Rotation, translation, and scaling invariant color image indexing. San Jose, CA: Proc. SPIE, Storage and Retrieval for Image and Video Databases VII; 3656: 623-630.
  • Celenk, M., Shao, Y. Printed color document storage and retrieval for image databases. Toronto, Canada: Proc. IS&T’s NIP 14: Int. Conf. Digital Printing Technologies; 298-301.
  • Celenk, M., Shao, Y. Object detection in color images using nonparametric Bayes classification and orthogonal functions. Orlando, FL: Proc. SPIE, Visual Information Processing VII; 3387: 147-155.
  • Celenk, M. A Bayesian approach to object detection in color images. Morgantown, WV: 30th Southeastern Symp. System Theory; 196-199.
  • Celenk, M., Uijt de Haag, M. Optimal thresholding for color images. San Jose, CA: Proc. SPIE, Nonlinear Image Processing IX; 3304: 250-259.
  • Celenk, M. Hierarchical color clustering for segmentation of textured images. Cookeville, TN: 29th Southeastern Symp. on System Theory; 483-487.
  • Celenk, M., Wu, J. Color image coding using bock truncation and vector quantization. Berlin, Germany: Int. Symp. Advanced Network Technologies.
  • Celenk, M. Textured surface identification in noisy color images. Orlando, FL: Visual Information Processing V, Proc. SPIE Vol.2753.
  • Celenk, M., Wu, J. Block truncation coding for color images using vector quantization. Orlando, FL: Hybrid Image and Signal Processing V, Proc. SPIE Vol.2751; 36-41.
  • Celenk, M. Color scene recognition using relational distance measurement. Orlando, FL: Visual Communications and Image Processing, Proc. SPIE Vol.2727; 229-240.
  • Celenk, M. Recognition of three-dimensional elastic volumes using cross-sections. San Jose, CA: Machine Vision Applications in Industrial Inspection IV; Proc. SPIE Vol.2665: 155-166.
  • Celenk, M. Relational graph representation of color images for model-based matching using relational distance measurement. Orlando, FL: Visual Information Processing IV; Proc. SPIE Vol.2488: 229-240.
  • Celenk, M. Three-dimensional object surface matching. Orlando, FL: Visual Information Processing IV; Proc. SPIE Vol.2488: 465-474.
  • Killeen, T., Celenk, M. Architectural support for interprocess communication. Indianapolis, IN: ISCA Int. Conf. Computer Applicat. in Engineering & Medicine; 36-40.
  • Celenk, M. Color scene matching. Mississippi State, MS: 27th Southeastern Symp. System Theory; 284-288.
  • Celenk, M., Wang, Y. Distributed computing in LANs and performance analysis. Indianapolis, IN: ISCA Int. Conf. Computer Applications in Engineering & Medicine; 162-166.
  • Killeen, T., Celenk, M. Improving inter-process communication through register windows. Mississippi State, MS: 27th Southeastern Symp. System Theory; 130-134.
  • Celenk, M., Chung, E. Novell Netware multimedia communications system using Microsoft windows. Mississippi State, MS: 27th Southeastern Symp. System Theory; 397-401.
  • Celenk, M., Wang, Y. Parallel task execution in LANs and performance analysis. Phoenix, AZ.: Fourth IEEE Int. Phoenix Conf. Computers and Comm.
  • Celenk, M. Three-dimensional object recognition using cross sections. Mississippi State, MS: 27th Southeastern Symp. System Theory; 92-96.
  • Celenk, M. Three-dimensional object shape recognition using cross-sections. Taipei, Taiwan: Visual Comm. & Image Processing; Proc. SPIE Vol.2501: 109-118.
  • Celenk, M. Three-dimensional object surface identification. San Jose, CA: Machine Vision Applications in Industrial Inspection III; SPIE Vol.2423: 136-147.
  • Celenk, M. Color scene representation for model-based matching. Boston, MA: Intell. Robots and Computer Vision XIII; Proc. SPIE Vol.2353: 537-548.
  • Killeen, T., Celenk, M. Shared-resource multistreaming processor architecture and performance analysis. Las Vegas, NV: 7th Int. Conf. Parallel & Distributed Computing Systems; 243-248.
  • Celenk, M., Wang, Y. Performance evaluation of the networks of workstations for parallel processing applications. Athens, OH: 26th Southeastern Symp. System Theory; 540-544.
  • Killeen, T., Celenk, M. Relocatable register sharing technique for multithreaded processor architectures. Athens, OH: 26th Southeastern Symp. System Theory; 545-549.
  • Celenk, M. Color scene analysis. San Jose, CA: Human Vision, Visual Processing, and Digital Display V; Proc. SPIE Vol.2179: 407-417.
  • Celenk, M. Color scene analysis in the 1976 CIE (L*,a*,b*) uniform color space. Scottsdale, AZ: First IS&T/SID Color Imaging Conference: Transforms & Transportability of Color; 208-218.
  • Celenk, M. Performance measurement of hypercube processors for vision applications. Louisville, KY: ISCA 6th Int. Conf. Parallel & Distributed Computing and Systems; 167-172.
  • Celenk, M. Optimal 3D object surface identification. Boston, MA: Intelligent Robots and Computer Vision XII; Proc. SPIE Vol. 2056: 132-143.
  • Wang, Y., Celenk, M. Parallel processing in the networks of workstations. Tuscaloosa, AL: 25th Southeastern Symp. System Theory; 442-446.
  • Killeen, T., Celenk, M. Stream-interleaved pipelined RISC processor design for SIMD and MIMD system development. Tuscaloosa, AL: 25th Southeastern Symp. System Theory; 452-456.
  • Celenk, M. New approach to optimal 3-D object surface matching. San Jose, CA: Image Modeling; Proc. SPIE Vol.1904: 2-13.
  • Chung, E., Celenk, M. Implementation of a Fax distribution system in the local area networks of PCs. Orlando, FL: IEEE Global Telecommunications Conf.; 2: 964-968.
  • Bachnak, R., Celenk, M. Applications of stereo vision to object reconstruction in industrial environments. Santa Fe, NM: Fourth Int. Symp. Robotics and Manufacturing; 4: 169-174.
  • Celenk, M., DiBenedetto, M., Rajendran, J. Implementation of DME/P critical area determination on message passing processors. DuPage County, IL: Int. Conf. Parallel Processing.
  • Celenk, M., DiBenedetto, M., Rajendran, J. DME/P critical area determination on message passing processors. Monterey, CA: IEEE Position Location and Navigation Symp.; 261-268.
  • Celenk, M., Mylvaganam, M. Implementation of BMLS computer model on hypercube systems. Monterey, CA: IEEE Position Location and Navigation Symp.; 375- 382.
  • Chung, E., Celenk, M. PC-based digital facsimile information distribution system. Greensboro, NC: 24th Southeastern Symp. System Theory; 596-600.
  • Celenk, M. Adaptive machine learning algorithm for multispectral image analysis. San Jose, CA: Color Hard Copy Graphic Arts; Proc. SPIE Vol.1670: 359-370.
  • Celenk, M., Moiz, S. Hadamard transform based object recognition using array processors. Orlando, FL: Applications of Artificial Intel. IX; Proc. SPIE Vol.1468: 764-775.
  • Celenk, M., Datari, S. Rotation invariant object classification using FFT features. Orlando, FL: Applications of Artificial Intelligence IX; Proc. SPIE Vol.1468: 752-763.
  • Celenk, M. Image template matching on hypercube array processors. Columbia, SC: 23rd Southeastern Symp. System Theory; 333-337.
  • Celenk, M., Reddy, V. Pipelined dynamic SISD system organization. Columbia, SC: 23rd Southeastern Symp.System Theory; 128-132.
  • Celenk, M., Sun, W. 3-D visual robot guidance in dynamic environment. Pittsburgh, PA: IEEE Int. Conf. Systems Engineering; 507-510.
  • Celenk, M., Bachnak, R. Multiple stereo vision system for 3-D object reconstruction. Pittsburgh, PA: Proc. IEEE Int. Conf. Systems Engineering; 555-558.
  • Bachnak, R., Celenk, M. 3-D object reconstruction from multiple views of a stereo-based vision system. Orlando, FL: Applications of Artificial Intelligence VIII; Proc. SPIE Vol.1293: 128-139.
  • Celenk, M., Sun, W. Visual robot guidance in 3D time varying environment. Orlando, FL: Applications of Artificial Intelligence VIII; Proc. SPIE Vol. 1293: 446-457.
  • Bachnak, R., Celenk, M. Triangulation-based camera calibration for machine vision systems. Philadelphia, PA: Visual Communications and Image Processing, Advances in Intelligent Robotics Systems.
  • Bachnak, R., Celenk, M. A stereo-based multiple camera system for 3-D information extraction in a robot workspace. Boston, MA: Int. Elect. Imag. Exp. & Conf.; 2: 857-862.
  • Celenk, M., Sun, W. Collision detection and path planning for a mobil robot in 3-D dynamic environment. Boston, MA: Int. Elect. Imaging Expos. & Conf.; 1: 594-599.
  • Celenk, M., Datari, S. Hypercube machine implementation of 2-D FFT algorithm for object recognition and visual inspection. Boston, MA: Int. Elect. Imaging Expos. & Conf.; 2: 1121-1126.
  • Bachnak, R., Celenk, M. A stereo system for 3-D measurements in robot workspaces. Albany, NY: Fourth IEEE Int. Symp. Intelligent Control.
  • Bachnak, R., Celenk, M. Matching of stereo image pairs for industrial vision systems. Dayton, OH: IEEE Int. Conf. Systems Engineering; 303-306.
  • Celenk, M., Lakshman, P. Object detection in industrial workstations using split-and-merge operation and parallel processing techniques. Dayton, OH: IEEE Int. Conf. Systems Engineering; 407-410.
  • Celenk, M., Bohora, A. Robot motion path planning in time-varying environment using quadtree data structure and parallel processing. Dayton, OH: IEEE Int. Conf. Systems Engineering; 313-316.
  • Celenk, M., Lim, C. Performance evaluation of hypercube array processor implementation of vision algorithms. Pasadena, CA: Int. Elect. Imaging Expos. & Conf.; 1: 380-385.
  • Celenk, M., Lim, C. Hypercube mapped ring and mesh implementation of low-level vision algorithms. Monterey, CA: 4th Conf. Hypercube Concurrent Comp. & Applic.
  • Celenk, M., Reza, H. Moving object tracking using local windows. Orlando, FL: Advan. in Image Comp.& Auto. Target Recog.; Proc. SPIE Vol.1099: 105-116.
  • Celenk, M., Lakshman, P. Parallel implementation of the split and merge algorithm on hypercube processors for object detection and identification. Orlando, FL: Applications of Artificial Intelligence VII; Proc. SPIE Vol. 1095: 251-262.
  • Celenk, M., Bohora, A. Visual robot guidance in dynamic environment using quadtree data structure and parallel processing. Orlando, FL: Applications of Artificial Intelligence VII; Proc. SPIE Vol. 1095: 435-446.
  • Bachnak, R., Celenk, M. A systematic corner finding algorithm for digital curves. Boston, MA: Int. Electronic Imaging Exposition and Conf.; 1: 188-193.
  • Celenk, M., LIm, C. Hypercube machine implementation of low-level vision algorithms. Boston, MA: Int. Elect. Imag. Expos.&Conf.; 2: 875-880.
  • Celenk, M., Reza, H. Motion analysis and description in time varying images. Boston, MA: Int. Electronic Imaging Exposition and Conf.; 1: 453-458.
  • Celenk, M., Reza, H. Moving object tracking in industrial work-stations. Houston, TX: ISA Int. Conf. Quantitative Measur. Through Image Proc.; 289-304.
  • Bachnak, R., Celenk, M. A corner detection based object representation technique for 2-D images. Arlington, VA: Third IEEE Int. Symp. IntelligentControl.
  • Celenk, M., Reza, H. Moving object tracking using local windows. Arlington, VA: Third IEEE Int. Symp. Intelligent Control.
  • Celenk, M. A recursive clustering technique for color picture segmentation. Ann Arbor, MI: IEEE Conf. Computer Vision & Pattern Recog.; 437-444.
  • Celenk, M. Dynamic feature space construction technique for computer vision systems. Orlando, FL: Applications of Artificial Intelligence VI; Proc. SPIE Vol. 937: 94-103.
  • Celenk, M., Bitar, R. Hazard detection in pipelined computers: A software approach. Columbus, OH: ISA/IEEE Symposium; 111-121.
  • Celenk, M., Reza, H. A systematic approach to motion analysis. Anaheim, CA: Int. Electronic Imaging Exposition and Conf.; 2: 764-768.
  • Celenk, M., Smith, S. Pattern recognition based computer vision system design for color image analysis. Anaheim, CA: Int. Elect. Imaging Exp. & Conf.; 1: 204-209.
  • Celenk, M., Smith, S. A design procedure for computer vision systems. Boston, MA: Int. Electronic Imaging Exposition and Conf.; 1: 124-127.
  • Celenk, M., Smith, S. A new feature extraction-selection method for color image analysis. Boston, MA: Int. Electronic Imaging Exposition and Conf.; 1: 115-119.
  • Celenk, M., Smith, S. An approach to color image partitioning. Boston, MA: Int. Electronic Imaging Exposition and Conf.; 1: 111-114.
  • Celenk, M. An adaptive machine learning algorithm for color image analysis and processing. Cambridge, MA: Int. Conf. Manufac. Science & Technology of the Future.
  • Celenk, M. A parametric training algorithm for image understanding systems. Orlando, FL: Applicat. of Artificial Intelligence V; Proc. SPIE Vol.786: 169-175.
  • Celenk, M. Modular design of the segmentation unit of hierarchical computer vision systems. Raleigh, NC: IEEE Int. Conf. Robotics and Automation; 1: 372-379.
  • Celenk, M., Smith, S. A spatial-spectral feature extraction technique for color images. Anaheim, CA: Int. Electronic Imaging Exposition and Conf.; 80-84.
  • Celenk, M., Smith, S. A systematic approach to color image segmentation. Anaheim, CA: Int. Electronic Imaging Exposition and Conf.; 76-79.
  • Celenk, M., Smith, S. A model for the segmentation unit of a computer vision system. Boston, MA: Int. Electronic Imaging Exposition and Conf.; 89-92.
  • Celenk, M., Smith, S. A spatial-spectral feature extraction technique for color images. Boston, MA: Int. Electronic Imaging Exposition and Conf.; 84-88.
  • Celenk, M., Smith, S. A systematic approach to color image segmentation. Boston, MA: Int. Electronic Imaging Exposition and Conf.; 80-83.
  • Celenk, M., Smith, S. Color image segmentation by clustering and parametric-histogramming technique. Paris, France: 8th Int. Conf. Pattern Recognition; 883-886.
  • Celenk, M., Smith, S. Dynamic architecture of the lower level processing unit of a computer vision system. Flims, Switzerland: 15th Int. Symp. Automotive Tech.& Automation; 2.
  • Celenk, M., Smith, S. Modeling of human color perception of visual patterns for feature extraction. Flims, Switzer.: 15th Int. Symp. Autom. Tech. & Autom.; 2.
  • Celenk, M., Smith, S. Gross segmentation of color images of natural scenes for Computer vision systems. Orlando, FL: Applications of Artificial Intelligence III; Proc. SPIE Vol. 635: 333-344.

Other (2)

  • Celenk, M. Pedestrian Collision Warning Demonstration Project.
  • Celenk, M. Road Surface Tracking and Black Ice Detection for Safe Transportation in Hazardous Driving Conditions.