A fast texture segmentation scheme based on active contours and discrete cosine transform. (August 2017) - Subudhi, Priyambada; Mukhopadhyay, Susanta
Highlights: A new external energy term used for parametric ACM for texture segmentation. It is based on features extracted from local block based DCT at contour and object points. Histograms built from quantized DCT coefficients in horizontal vertical diagonal directions. Wassertein distance metric used to find heterogeneity between object and contour. Graphical abstract: Abstract: This paper presents a novel and efficient parametric active contour model based on the texture describing properties derived from coefficients of the two-dimensional Discrete Cosine Transform (2-D DCT) for segmenting texture objects against complex backgrounds. Block based 2-D DCT is applied in the local neighbourhood of all the contour control points and some randomly chosen object points. DCT coefficients in the horizontal, vertical and diagonal directions which represent the dominant textures are used to construct the histograms those exhibit different structures for different texture regions. Heterogeneity of these histograms corresponding to contour and object points is measured by Wasserstein distance metric. Finally, DC coefficient which represents the energy of the corresponding block modulated by the calculated Wasserstein distance is employed as the external energy of the proposed active contour model. Experiments on synthetic and natural texture images show the efficiency of our model in terms of accuracy and speed.