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首页> 外文期刊>International Journal of Pattern Recognition and Artificial Intelligence >COMPUTING IMAGE TEXTURE BY ISOPATTERN
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COMPUTING IMAGE TEXTURE BY ISOPATTERN

机译：通过ISOPATTERN计算图像纹理

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摘要

Texture is an important feature that aids in identifying objects of interest or region of interest irrespective of the source of the image. In this paper, a novel and simple isopattern-based texture feature is introduced. Spatial gray scale dependencies represented by bit plane is analyzed for specific patterns and are accumulated in bins. These are scaled by half-normal weighting function to provide isopattern texture feature. The ability of this texture feature in capturing textural variations of the images despite the presence of illumination, scale and rotation is demonstrated by conducting texture analysis on Brodatz, OuTex texture datasets and its classification accuracy on Kylberg dataset. The results of these two experimentation indicate that the proposed textural feature picks variation in texture significantly and has a better texture classification accuracy of 98.26% when compared with the state-of-the-art features like Gabor, GLCM and LBP.
机译：纹理是一个重要特征，可帮助识别感兴趣的对象或感兴趣的区域，而与图像的来源无关。本文介绍了一种新颖且简单的基于等图模式的纹理特征。分析位平面表示的空间灰度依赖性，以获取特定模式并将其累积在bin中。这些可以通过半正常加权功能进行缩放，以提供等图面纹理功能。通过在Brodatz，OuTex纹理数据集上进行纹理分析及其在Kylberg数据集上的分类精度，证明了这种纹理特征在捕获图像纹理变化的能力（尽管存在照明，缩放和旋转）的能力。这两个实验的结果表明，与最新的Gabor，GLCM和LBP等特征相比，拟议的纹理特征在纹理上表现出明显的变化，并且具有98.26％的更好的纹理分类精度。

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