Classifying natural images into a subjective groups is a challenging task in image processing. This paper deals with the fuzzy rule based classification of greenery and non-greenery images using guided gray level coherence features (GGLCFs). Coherence vector is constructed for each input gray level images and is used to construct three GGLCFs namely and using one or more guide images. These GGLCFs are converted into fuzzy features and fuzzy rules are constructed by learning from the training set of images using adaptive neuro fuzzy inference system. The performance of the system is illustrated using 600 images consisting of both greenery and non-greenery images.

fuzzy rule based classification, guided gray level coherence features, greenery images.