IJIGSP Vol. 4, No. 12, 8 Nov. 2012
Cover page and Table of Contents: PDF (size: 402KB)
Full Text (PDF, 402KB), PP.19-25
Views: 0 Downloads: 0
Real-time Color Image Edge Detection, Sobel Operator, FPGA Implementation, VLSI Architecture, Color Edge Detection Processor
Color Image edge detection is very basic and important step for many applications such as image segmentation, image analysis, facial analysis, objects identifications/tracking and many others. The main challenge for real-time implementation of color image edge detection is because of high volume of data to be processed (3 times as compared to gray images). This paper describes the real-time implementation of Sobel operator based color image edge detection using FPGA. Sobel operator is chosen for edge detection due to its property to counteract the noise sensitivity of the simple gradient operator. In order to achieve real-time performance, a parallel architecture is designed, which uses three processing elements to compute edge maps of R, G, and B color components. The architecture is coded using VHDL, simulated in ModelSim, synthesized using Xilinx ISE 10.1 and implemented on Xilinx ML510 (Virtex-5 FX130T) FPGA platform. The complete system is working at 27 MHz clock frequency. The measured performance of our system for standard PAL (720x576) size images is 50 fps (frames per second) and CIF (352x288) size images is 200 fps.
Sanjay Singh,Anil Kumar Saini,Ravi Saini,"Real-time FPGA Based Implementation of Color Image Edge Detection", IJIGSP, vol.4, no.12, pp.19-25, 2012. DOI: 10.5815/ijigsp.2012.12.03
[1]H. Jiang, H. Ardo, and V. Owall (2009), A Hardware Architecture for Real-Time Video Segmentation Utilizing Memory Reduction Techniques, IEEE Transactions on Circuits and Systems for Video Technology, vol. 19, no. 2, pp. 226–236.
[2]R.L. Rosas, A.D. Luca, and F.B. Santillan (2005), SIMD Architecture for Image Segmentation using Sobel Operators Implemented in FPGA Technology, In Proceedings of 2nd International Conference on Electrical and Electronics Engineering, pp. 77-80.
[3]T.A. Abbasi and M.U. Abbasi (2007), A Novel FPGA-based Architecture for Sobel Edge Detection Operator, International Journal of Electronics, vol. 94, no. 9, pp. 889-896, 2007.
[4]Z.E.M. Osman, F.A. Hussin, And N.B.Z. Ali (2010a), Hardware Implementation of an Optimized Processor Architecture for Sobel Image Edge Detection Operator, In Proceeding of International Conference on Intelligent and Advanced Systems (ICIAS), pp. 1-4.
[5]Z.E.M. Osman, F.A. Hussin, And N.B.Z. Ali (2010b), Optimization of Processor Architecture for Image Edge Detection Filter, In Proceeding of International Conference on Computer Modeling and Simulation, pp. 648-652
[6]I. Yasri, N.H. Hamid, And V.V. Yap (2008), Performance Analysis of FPGA based Sobel Edge Detection Operator, In Proceedings of International Conference on Electronic Design, pp. 1-4.
[7]V. Sanduja and R. Patial (2012), Sobel Edge Detection using Parallel Architecture based on FPGA, International Journal of Applied Information Systems, vol. 3, no. 4, pp. 20-24.
[8]G. Anusha, T.J. Prasad, and D.S. Narayana (2012), Implementation of SOBEL Edge Detection on FPGA, International Journal of Computer Trends and Technology, vol. 3, no. 3, pp. 472-475.
[9]L.P. Latha (2012), Design of Edge Detection Technique Using FPGA (Field Programmable Gate Array) and DSP (Digital Signal Processor), VSRD International Journal of Electrical, Electronics & Communication Engineering, vol. 2, no. 6, pp. 346-352.
[10]A.R. Ibrahim, N.A. Wahed, N. Shinwari, and M.A. Nasser (2011), Hardware Implementation of Real Time Video Edge Detection With Adjustable Threshold Level (Edge Sharpness) Using Xilinx Spartan-3A FPGA, Report.
[11]P.S. Chikkali and K. Prabhushetty (2011), FPGA based Image Edge Detection and Segmentation, International Journal of Advanced Engineering Sciences and Technologies, Vol. 9, Issue 2, pp. 187-192.
[12]R. Harinarayan, R. Pannerselvam, M.M. Ali, And D.K. Tripathi (2011), Feature extraction of Digital Aerial Images by FPGA based implementation of edge detection algorithms, In Proceedings of International Conference on Emerging Trends in Electrical and Computer Technology, pp. 631-635.
[13]K.C. Sudeep and J. Majumdar (2011), A Novel Architecture for Real Time Implementation of Edge Detectors on FPGA, International Journal of Computer Science Issues, vol. 8, no. 1, pp. 193-202.
[14]W. Burger and M.J. Burge (2008), Digital Image Processing: An Algorithmic Introduction Using Java, New York: Springer, 120-123.
[15]R.C. Gonzalez, and R.E. Woods (2009), Digital Image Processing, India: Pearson Education, Inc., 187-190.
[16]M.A. Ruzon, A Short History of Color Edge Detection. http://ai.stanford.edu/~ruzon/compass/color.html
[17]S. Singh, A.K. Saini, R. Saini, A.S. Mandal, C. Shekhar, and A. Vohra (2012), Real-time Video Acquisition and PTZ Camera Movement Control for FPGA based Automated Video Surveillance System, International Journal of Research & Reviews in Computer Science, Vol. 3, No. 2, pp. 1572-1575.
[18]C. Moore, H. Devos, and D. Stroobandt (2009), Optimizing the FPGA Memory Design for a Sobel Edge Detector, In Proceedings of 20th Annual Workshop on Circuits, Systems and Signal Processing, pp. 496-499.
[19]Z. Vasicek, and L. Sekanina (2008), Novel Hardware Implementation of Adaptive Median Filters, In Proceedings of 11th IEEE workshop on Design and Diagnostics of Electronic Circuits and Systems, pp. 1-6.