Tsallis Entropy Thresholding Based on Multi-scale andMulti-direction Gabor Transform

To deal with automatic threshold selection issue in non-modal, unimodal, bimodal or multimodalsituations within a unified framework, a Tsallis Entropy thresholding segmentation method based on Multi-scale and multi-direction Gabor transform (MGTE) is proposed. The multi-scale product image is first obtainedby the Gabor transform and then the inner and outer contour images are used to reconstruct the one-dimensional histogram from the multi-scale product image. Based on the reconstruction of the one-dimensionalhistogram, the Tsallis entropy calculation model is utilized to select 4 thresholds by maximizing Tsallis entropyin 4 different directions, and finally the weighted sum of the 4 thresholds is used as the final threshold. Theproposed method is compared with 5 segmentation methods on 4 synthetic images and 40 real-world images.The results show that the proposed method has no advantage in computational efficiency, but its adaptabilityand segmentation accuracy are significantly improved.