Enhancement of Corn image quality using Very-Deep Super-Resolution (VDSR) neural network

Machine vision based quality inspection of food items is dependent on the quality of the acquired images. However, acquisition of high quality images requires costly and complex camera or other image acquisition equipment. In this paper, we have proposed a deep learning based solution which can be used to increase the resolution of input data acquired by low cost camera systems. The benefit of the proposed work lies in the fact that the input data acquired at lower resolution may be processed to obtain higher resolution suitable for detecting minute defects in agricultural products. Our proposed method was found to perform better than existing methods in terms of accuracy and visual appearance improvements.