VLSI Implementation of Reconfigurable Canny Edge Detection Algorithm

Real-time video and image processing are used in various industrial, medical, consumer electronics and embedded device applications. These applications typically demonstrate an increasing demand for computing power and system complexity. Hence, edge detection is the most common and widely used technique in image or video processing applications. Several traditional canny edge detection methods use fixed thresholding techniques to compare the pixel values. This sacrifices the edge detection performance and increases the computational complexity. Hence, the Canny Edge detection algorithm is preferred to enhance the image quality with reduced complexity. They adjust the quality of the image by manipulating the Sigma and Threshold parameters and detect the edges accurately by eliminating the noise. The reconfigurable canny edge detection algorithm presents a procedure for detecting edges without multipliers. The new algorithm uses a low-complex, non-uniform histogram gradient to compute thresholds and variable sigma values that replace the add and shift operator instead of multipliers to reduce the area and sigma. The simulation is done in the ModelSim platform using VHDL code which results in the output of bit sequences. By comparing the results of the reconfigurable canny edge detection and traditional algorithm, the new algorithm’s performance can be observed with improvements of around 21% and 80% for consumed power and delay parameters respectively.