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A Systolic Image Difference Algorithm for RLE-Compressed Images
May 2000 (vol. 11 no. 5)
pp. 433-443

Abstract—A new systolic algorithm which computes image differences in run-length encoded (RLE) format is described. The binary image difference operation is commonly used in many image processing applications including automated inspection systems, character recognition, fingerprint analysis, and motion detection. The efficiency of these operations can be improved significantly with the availability of a fast systolic system that computes the image difference as described in this paper. It is shown that for images with a high similarity measure, the time complexity of the systolic algorithm is small and, in some cases, constant with respect to the image size. A formal proof of correctness for the algorithm is also given.

[1] P.P. Jonker and E.R. Komen, “A Scalable Real-Time Image Processing Pipeline,” Proc. 11th Int'l Conf. Pattern Recognition (IAPR), vol. 4, 1992. Conference D: Architectures for Vision and Pattern Recognition, pp. 142–146.
[2] F. Ercal, F. Bunyak, F. Hao, and L. Zheng, “A Fast Modular RLE-Based Inspection Scheme for PCBs,” Proc. Int'l Society for Optical Eng., (SPIE)—Architectures, Networks, and Intelligent Systems for Manufacturing Integration, vol. 3,203, pp. 49–59, Oct. 1997.
[3] S. Gil, R. Milanese, and T. Pun, “Comparing Features for Target Tracking in Traffic Scenes,” Pattern Recognition, vol. 29, no. 8, pp. 1,285–1,296, 1996.
[4] H. Kawasumi, H. Sekii, N. Enomoto, H. Ohata, and A. Okazaki, “Detecting Intruders using Time-Series Data by Projection Pattern of Silhouette,” Electrical Engineering in Japan, vol. 119, no. 1, pp. 62–73, 1997.
[5] G.M. Emelyanov, N.V. Kurmyshev, and O.Y. Yuvzhik, “Procedures and Algorithms for Detecting and Determining the Orientation of Objects in Binary Images,” Pattern Recognition and Image Analysis, vol. 7, no. 3 pp. 373–378, 1997.
[6] G. Agam, J. Frydman, O. Amiram, and I. Dinstein, “Efficient Morphological Processing of Maps and Line-Drawings Based on Directional Interval Coding,” Proc. SPIE—The Int'l Soc. for Optical Eng., vol. 3,168 pp. 41–51, 1997.
[7] N.K. Ratha, A.K. Jain, and D.T. Rover, "Convolution on Splash 2," Proc. IEEE Symp. FPGAs for Custom Computing Machines, pp. 204-213,Napa Valley, Calif., 1995.
[8] A. Rasquinha and N. Ranganathan, “C3L: A Chip for Connected Component Labelling,” IEEE 10th International Conf. VLSI Design, pp. 446–51, Jan. 1997.
[9] M. Djunatan and T. Mengko, “A Programmable Real-Time Systolic Processor Architecture for Image Morphological Operations, Binary Template Matching and Min/Max Filtering,” 1991 IEEE Int'l Symp. Circuits and Systems, vol. 1, pp. 65–68, 1991.
[10] N. Ranganathan and K.B. Doreswamy, “A Systolic Algorithm and Architecture for Image Thinning,” Proc. 5th Great Lakes Symp. VLSI, Mar 1995.
[11] V. Kumar, A. Grama, A. Gupta, and G. Karypis, Introduction to Parallel Computing: Design and Analysis of Algorithms. Benjamin Cummings, 1994.
[12] Y. Ben-Asher,D. Peleg,R. Ramaswami,, and A. Schuster,“The power of reconfiguration,” J. of Parallel and Distributed Computing, vol. 13, no. 2, pp. 139-153, Oct. 1991.
[13] F. Ercal, H. Pottinger, V.S. Balakrishnan, and M. Agarwal, “Design and Implementation of a Systolic Array Based RLE Image Processor Using an FPGA,” detail.html.
[14] J.V. Oldfield and R.C. Dorf, Field Programmable Gate Arrays. John Wiley and Sons, Inc., 1995.

Index Terms:
Systolic algorithm, image difference, image compression, run-length encoding.
Fikret Ercal, Mark Allen, Hao Feng, "A Systolic Image Difference Algorithm for RLE-Compressed Images," IEEE Transactions on Parallel and Distributed Systems, vol. 11, no. 5, pp. 433-443, May 2000, doi:10.1109/71.852397
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