MACHINE VISION FOR WEED DETECTION IN VEGETABLE CROP USING MODIFIED SUPPORT VECTOR MACHINE

Weed plants are unwanted plants growing in between host plants. There are more than 8000 weed species in agriculture field. This is the global issues which leads to loss in both the quality and quantity of the product. So, attention has to be taken in prior time to avoid these losses and saving manpower. In this paper, the three procedures such as segmentation, feature extraction and classification, for weed plant identification were presented in detail. To separate the region of interest threshold segmentation method was applied. Then the important features such as shape and textures were analysed with the help of GLCM method which were discussed in this review. Finally, in the image classification method namely modified support vector machine was used to separate the weed and host plants.