FPGA based DBRAM-CED Method for Lung Cancer Detection

In the Digital Image processing, discovering the boundaries of the objects in the image is one of the important stage for computer vision applications. There are different kinds of Edge Detection (ED) techniques available such as Canny, Laplacian, Log Operator, Sobel etc. From the analysis, It is found that Canny Edge Detector (CED) provides better results in comparison with other edge detectors. In this paper, hardware architecture for CED has been introduced, which is named as DBRAM-CED. In order to improve the ED performance, Dual port Block Random Access Memory (DBRAM) is used. The hardware analysis of the performance parameters such as LUT, flip flop, slices and frequency are measured.