COMPARISON OF EDGE DETECTION METHODS USING ROBERTS AND LAPLACIAN OPERATORS ON MANGO LEAF OBJECTS

Abstract

Edge detection is a technique to find the outlines of an object in an image by detecting significant changes in brightness or discontinuities. This study discusses the comparison of edge detection using Roberts operators and Laplacian operators. The object used in edge detection is four types of mango leaves (Golek, Arum Manis, Madu, and Kuweni) with the *.jpeg format that has been pre-processed with 1000 x 278 pixels. The test used in this study compared the results of White Pixel values, MSE, and PSNR with test data as many as 24 data samples from four types of mango leaves. The results of the comparison of edge detection methods using the Laplacian operator get the lowest MSE value of 7.8577, the highest PSNR value of 39.2119, and the white pixel value of 164951, while the Roberts operator gets the lowest MSE value of 8.9723, the highest PSNR value of 38.6358, and the white pixel value of 155889.

Keywords

• edge detection
• laplacian
• roberts