Novel method for weed classification in maize field using Otsu and PCA implementation

This paper proposes two methods; oriented to crop row detection in images from agriculture fields with high weed pressure and to further distinguish between weed and crop. Firstly, for crop row detection the image processing consists of three main processes: image segmentation, double thresholding based on the 3D-Otsu's method, and crop row detection. Secondly, further classification between weed and crop, is carried out by compressing the three dimension vectors of an image to one dimension using the principal component analysis (PCA) method. Finally the combination of Otsu method and the PCA enable us to not only detect weed in crop rows but also classify this weed from crop. Hence it is better suited for the real time applications pertaining to weed detection.