Local binary patterns (LBPs) are used for effective texture representation in various applications. This study explores the clustering consistency and stability of image segmentation when distance-based clustering methods are used with an LBP. Because data are described by features and attributes, distances among data are also dominated by the definition of features. Moreover, four popular LBP encoding schemes for segmenting computed tomography (CT) images by using fuzzy C-means are discussed and compared. The experimental results demonstrate several notable phenomena: When the pixels are encoded in different LBP encoding schemes, the distance between these pixels varies considerably. The experimental results indicate that each LBP encoding scheme emphasizes a specific image texture that dominates how pixels are described in the feature space and thus affects the clustering results. Based on the evaluation of CT image segmentation by using the clustering inconsistency index, linear and corner-like LBPs are particularly suitable for clustering longitudinal sections and cross sections of CT images, respectively.

中文翻译：

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计算机断层扫描图像分割的局部二进制模式编码方案：实验和比较研究

局部二进制模式 (LBP) 用于在各种应用中进行有效的纹理表示。本研究探讨了基于距离的聚类方法与 LBP 一起使用时图像分割的聚类一致性和稳定性。因为数据是由特征和属性描述的，数据之间的距离也由特征的定义决定。此外，讨论和比较了四种流行的 LBP 编码方案，用于使用模糊 C 均值分割计算机断层扫描 (CT) 图像。实验结果证明了几个值得注意的现象：当像素以不同的 LBP 编码方案进行编码时，这些像素之间的距离变化很大。实验结果表明，每种 LBP 编码方案都强调特定的图像纹理，该纹理支配着特征空间中像素的描述方式，从而影响聚类结果。基于聚类不一致性指数对CT图像分割的评价，线状LBP和角状LBP分别特别适合对CT图像的纵向截面和横截面进行聚类。