IMAGE RECOGNITION USING MORPHOLOGICAL OPERATIONS

Abstract

Image matching using morphological operations is a research point that combines the pattem recognition and image morphological processing which can successfully be used in pattem classification tasks. A technique for investigating and studying the problem of estimating the similarity between images is presented in this thesis. The proposed technique is applied to the similarity measure of both the binary and gray­ scale images. The shape representation for this new method utilizes morphological image opening and closing of the input image at different scales of a primary and rotated structuring elements. The areas of the opened and closed images are computed for each scale of the structuring element to construct the feature vector of each input image. This feature vector is called morphological descriptor.

The drawback of shape representation techniques based on processmg single complex shape is that the extraction of complex shape properties may not be efficient. So, the proposed shape representation technique described is based on the decomposition of a complex shape to multiple simple signature shapes. The idea of this approach is to process decomposed, multiple shapes instead of processing the original shape.