Image Segmentation on Gabor Filtered images using Projective Transformation

In recent years, image segmentation has been applied on various images for obtaining various results. They are being deployed in numerous applications. There are lot of techniques adopted to make the image distortion free. Methods are also applied when the original image needs to be extracted from the image containing the background. Projective transformation is one of the techniques where we can apply phase correlation among the images and segment the part of the image that is needed for the next processing step. In this proposed work, we have deployed a model where an input image is given. The image is then undergone into various scaling techniques. Use of active contours and graph cut methods are embedded to obtain the segmented image. The key role of this model is to apply the Gabor filters and perform projective transformation among the image to segment the original part of the image from its background. The results are proposed by giving an output in a binary form. The work runs for a maximum of 100 iterations and for that the relaxation factor is taken as 0.5.