Unsupervised texture analysis using a robust stochastic image model

Kim, K.H.; Sharif, B.S.; Chester, E.G.

doi:10.1049/cp:19970967

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“…Model based texture measures construct an image model which is based on the original image to describe the texture. Gibbs Markov Random Field (GMRF) [15] and Auto Regressive model [16] are some examples for model based texture measurement. Markov Random Field assumes that the intensity at each pixel in the image depends on the intensities of only neighboring pixels whereas Auto Regressive model approximates a pixel in an image as the linear combination of its local neighbors.…”

Section: Introductionmentioning

confidence: 99%

Segmentation of Multi-Textured Images using Optimized Local Ternary Patterns

Raja¹,

Sadasivam²

2014

IJCA

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Texture segmentation is a process of segmenting an image into differently textured regions. This paper is aimed at the segmentation of multitextured images by using Optimized Local Ternary Patterns (OLTP), a new texture model which is recently proposed for texture analysis. This paper uses unsupervised texture segmentation method with the application of optimized local ternary patterns for finding the dissimilarity of adjacent image regions during the segmentation process. The performance of this recently proposed texture measure OLTP is evaluated, compared with other texture models Texture Spectrum (TS) and Local Binary Patterns (LBP) and found to be the best.

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Section: Introductionmentioning

confidence: 99%