access icon free Texture-based image segmentation using neutrosophic clustering

This study presents an effective segmentation method which is based on neutrosophic clustering with the integration of texture features for images. The proposed method transforms the image into the neutrosophic domain and then extracts the texture features using analogies of human preattentive texture discrimination mechanisms. Finally, the neutrosophic clustering is employed to segment the images. This method can handle the indeterminacy of pixels to have strong clusters and to perform segmentation effectively with the noisy images. Experiments are performed with various types of natural and medical images to exhibit the performance of proposed segmentation method. The evaluation of proposed method has been done with other segmentation methods to measure its performance which shows its robustness for noisy and textured images.

Inspec keywords: image segmentation; image texture

Other keywords: human preattentive texture discrimination mechanisms; texture-based image segmentation; texture features; neutrosophic clustering

Subjects: Optical, image and video signal processing; Computer vision and image processing techniques

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