ABSTRACT
Image processing techniques are one of the fastest developing technologies in the current world. These techniques encompass generic enhancement operations on images that make images viable for extractions of required information (Maier et al., 2019; Fernández-Pacheco et al., 2014). They are core research areas within the disciplines of engineering and computer sciences. Computer algorithms essentially process digital images using various tasks including reconstructions, restorations, compressions, enhancements, estimations of spectrums in images. Executions of these tasks result in analyses or classifications or detections of objects in digital images. Though image processing techniques can contribute towards growth of agriculture and specifically in determining weeds in cultivations, classification of weeds from images is a huge challenge. This chapter details on classification of crops and weeds using image processing techniques while focusing on improving classification accuracies using preprocessing, feature extractions, optimizations of feature selections, classifications, and deep learning approaches.