Color and texture image segmentation using uniform local binary patterns

• Autorzy: Arasteh S. , Hung C. C.
• Konferencja: International Conference on Computer Vision and Graphics ICCVG 2006 (25-27.09.2006 ; Warsaw, Poland)
• Języki publikacji: EN

Abstrakty

EN

The paper describes a new algorithm for image segmentation based on the color and texture features. The Uniform Local Binary Pattern (ULBP) method is used to extract texture features. Color features are defined based on the pixels' color bands. Image segmentation is carried out using the K-means algorithm on feature vectors, including color and texture features. The distance measure is defined as a function of the color and texture feature vector distances from the K-means defined centers. The weighting parameter is used to adjust the relative contribution of the color and texture features. The proposed algorithm is applied to color images in the RGB, HSV and IHLS color spaces. Experimental results show that the proposed algorithm yields good performance in combining color and texture features to distinguish different texture patterns. In particular, for textures with high color contrast, the results are prominent. The main advantage of the method is its speed and simplicity, which are inherited from the K-means algorithm.

Słowa kluczowe

EN

color and texture segmentation; local binary patterns

• Wydawca: Institute of Information Technology of the Warsaw University of Life Sciences – SGGW
• Czasopismo: Machine Graphics and Vision
• Rocznik: 2006
• Tom: Vol. 15, No. 3/4
• Strony: 265--274
• Opis fizyczny: Bibliogr. 19 poz., tab., il.

Twórcy

autor

Arasteh S.

autor

Hung C. C.

• School of Computing and Software Engineering, Southern Polytechnic State University, Marietta, GA, 30060-2896,

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