Real-time Hevea Leaves Diseases Identification using Sobel Edge Algorithm on FPGA: A Preliminary Study

Abstract

Real-time image processing is related with typical frame rate that required processing all the frames as soon as the image is captured. Fast processing time is required for edge detection since it is needed to be carry out in a real time. This paper proposes a real-time edge detection technique for identifying Hevea leaves diseases (rubber tree leaves) in images and its hardware implementation. Three major Hevea leaves diseases which are Corynespora Leaf Spot, Bird's Eye Leaf Spot and Collectotrichum Leaf Disease used in this study for image comparison. The disease on the leaves can be detected through edge detection by using Sobel edge detection algorithm. The realtime edge detection result generated by FPGA Cyclone IV E which is displayed through a monitor is compared to Sobel edge detection algorithm that is generated with MATLAB. The algorithm has been implemented on FPGA and the image results on the VGA monitor are similar as the simulation on the MATLAB.