The optical texture of coke is undoubtedly one of the important factors that determined many properties of coke, but it still mostly depends on the skills and experience of manual analysis. In this paper, a novel automatic measurement method is proposed for coke optical texture. this method through two analyzer angle images(10° and 170°) under polarizing microscope to recognize isochromatic regions which occurs color changed between blue and red by image processing, then characterize the dimensional sizes of isochromatic regions and classify them into different anisotropic texture type. Two fitted ellipse methods are used to characterize the regions' dimensional sizes by the range of shape factor S, followed by classifying different types of anisotropic texture according to the long and short axes of fitted ellipse. An automatic image acquisition and analysis system is established based on the above method. Finally, eight coke samples derived from different ranks of coking coal were selected to test the proposed method. The result shows that it can effectively recognize different types of anisotropic texture and provide composition of different anisotropic texture type for each coke. Moreover, the anisotropic degree of coke shows a significant positive correlation with parent coal rank and a negative correlation with coke reactivity index (CRI).

中文翻译：

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焦炭光学织构测量新方法及对不同等级炼焦煤焦的应用

焦炭的光学质地无疑是决定焦炭许多性质的重要因素之一，但仍主要取决于人工分析的技巧和经验。本文提出了一种新的焦炭光学质地自动测量方法。该方法通过偏光显微镜下的两个分析角图像（10°和170°），通过图像处理识别发生蓝色和红色之间颜色变化的等色区域，然后表征等色区域的尺寸大小，并将其分类为不同的各向异性纹理类型。两种拟合椭圆方法用于通过形状因子S的范围来表征区域的尺寸大小，然后根据拟合椭圆的长短轴对不同类型的各向异性纹理进行分类。基于上述方法建立了自动图像采集与分析系统。最后，选择了来自不同等级炼焦煤的八个焦炭样品来测试所提出的方法。结果表明，它可以有效识别不同类型的各向异性织构，并为每种焦炭提供不同的各向异性织构类型组成。此外，焦炭各向异性程度与母煤等级呈显着正相关，与焦炭反应性指数（CRI）呈负相关。