Video Image Segmentation with Texture Gradient using DT-CWT and Spectral Clustering

A fast and automatic video object segmentation algorithm based on wavelet transform is proposed in this paper. For some applications the whole image cannot be processed directly because it is inefficient and impractical. Segmentation results in a set of images that cover the entire image. This work proposes a two stage segmentation method, which effectively process both the textured and non-textured regions. Dual Tree Complex Wavelet Transform, an extension of discrete wavelet transform, extracts texture feature from the image and orientation median filtering reduces the double edge effect at the texture edges. Watershed transform of Gaussian gradient of combined texture and non-texture feature give the first stage segmentation. The initial segmentation into super-pixels reduces computational burden and the second stage uses spectral clustering technique to cluster these primitive regions. The proposed algorithm is robust to the entire motion and local deformation of object.