Weed growth and intrusion detection by multi angle images of vegetable plants using modified SVD

The requirement of earlier identification of weed growth and plant disease is one of the most important procedures in precision agriculture. In this research work we identified the best method of positioning the optical sensors to get the best possible images. To address this purpose the variant of SVD is used for feature construction. Our proposed approach optimize and reiterate our similar earlier findings in identification of plants. The threshold augmentation technique is used to find the inter and intra average differences for both aerial and portrait angle images for comparison. The intrusion detection software Matlab is created and tested for the Portrait images and compared with aerial images. The Portrait images to find the intrusion are found better than aerial images in number of trails 15% more than the aerial images.