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.
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机译：彩色图像边缘检测对于许多应用程序来说是非常基本和重要的步骤，例如图像分割，图像分析，面部分析，物体识别/跟踪等。实时执行彩色图像边缘检测的主要挑战是因为要处理的数据量很大（是灰度图像的3倍）。本文介绍了使用FPGA实时实现基于Sobel算子的彩色图像边缘检测。选择Sobel算子进行边缘检测是因为它具有抵消简单梯度算子的噪声敏感性的特性。为了实现实时性能，设计了一种并行体系结构，该体系结构使用三个处理元素来计算R，G和B颜色分量的边缘图。该架构使用VHDL编码，在ModelSim中进行仿真，使用Xilinx ISE 10.1进行综合，并在Xilinx ML510（Virtex-5 FX130T）FPGA平台上实现。整个系统以27 MHz的时钟频率工作。对于标准PAL（720x576）大小的图像，我们系统的测量性能为50 fps（每秒帧），而CIF（352x288）大小的图像为200 fps。
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