Paper
26 July 2018 Statistical multi-scale laws’ texture energy for texture segmentation
Author Affiliations +
Proceedings Volume 10828, Third International Workshop on Pattern Recognition; 108280I (2018) https://doi.org/10.1117/12.2501914
Event: Third International Workshop on Pattern Recognition, 2018, Jinan, China
Abstract
Nowadays it is one of the main focuses to recognize objects in a digital image. The texture is an important valuable feature in describing the coarseness and the regularity pattern in the surface of an object. We present an interesting and effective technique for segmentation of different texture by integrating color information and Laws’ texture energy. The first step is to convert an image from RGB to HSV color space to obtain hue channel as the basic feature. The second step is to calculate Laws’ texture energy in each pixel by exploring statistical approaches including mean and variance in the serial of multi-scale windows by moving window, in this step several variances can be produced to form a vector, and the vector can be used as an additional feature. This work utilizes threshold of difference between neighborhood vectors as an alternative to distinguish coarseness in a region after segmentation by using the basic feature. In addition, this work calculates the difference mean of hue each color in a region which contain many colors in 5 × 5 window size and utilizes threshold of mean to distinguish the similarity mean between colors. This work examined images from Berkeley Segmentation Dataset (BSDS) which have several textures by using a threshold of difference (70) between neighborhood vectors and threshold mean (10) of hue. The results show that 70.6% of the texture segmentation can be accepted after combining color information and Laws’ texture energy and provide a favorable result for texture segmentation.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mega Kusuma Wardhani, Xiangru Yu, and Jinping Li "Statistical multi-scale laws’ texture energy for texture segmentation", Proc. SPIE 10828, Third International Workshop on Pattern Recognition, 108280I (26 July 2018); https://doi.org/10.1117/12.2501914
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Cited by 2 scholarly publications.
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KEYWORDS
Image segmentation

RGB color model

Feature extraction

Image classification

Image analysis

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