Weed Detection Using Textural Image Analysis

Abstract

The objective of the work described here was to detect broad-leaved weeds in grassland. We used textural image analysis to detect weeds in grass. In the textural analysis, images were divided in square tiles, which were subjected to a 2-D FFT. The power of the resulting spectrum was found to be a measure of the presence of coarse elements (weeds). Application of a threshold made it possible to classify tiles as containing only grass or as containing a weed. A weed was assumed to be detected when a sufficient number of adjacent tiles were classified as containing weed material. The algorithm has a success rate of 94%