Pest Detection using Adaptive Thresholding

Pest detection is crucial to secure crops and ensure food quality. A lot of work is being carried out for the effective identification of pests. In this paper we will develop a novel and fast methodology to detect and enumerate the pests present in an image using rapid feature detection algorithm. The amount of pesticides being used for agriculture pollutes the environment, with sophisticated machine vision systems that implement this algorithm we can make machines that utilize pesticides effectively by selective targeting pests using image processing. In the current scenario, human labor is used for the manual detection of pests which is not highly accurate. Automation is required in this field as it would be accurate in the detection of pests in crops. This paper proposes a system that would automate the detection of pests in crops using digital image processing techniques.