EDGE DETECTION IMAGE OPERATORS IN HEXAGONAL PIXEL FRAMEWORK

With the advancement in computer vision and image processing field and due to the high computing power of graphic devices, it is high time to think of an alternate sampling grid called hexagonal grid which exactly resembles our rods and cones in the photoreceptors of human retina(eyes). Hexagonal grid structure framework provides higher angular resolution, equidistant property and consistent connectivity. As the angular resolution is more in hexagonal grid, curved structures can be well represented in hexagonal grid. As there is no hexagonal capturing and display device, software simulation methods are used for hexagonal image processing before proceeding the edge detection in hexagonal framework. Edge detection algorithm is the cornerstone for many pre-processing task in image processing field This paper covers different edge detection algorithms like robert, sobel, prewitt, log and canny in hexagonal and rectangular grid and the performance is assessed based on the design metrics like PSNR (peak signal to noise ratio) and MSE (mean square error). For all edge detection algorithms, results shows that hexagonal structural framework outperforms rectangular grid framework.