On texture classification
On texture classification
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DOI：
10.1080/00207729708929427
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发表时间：
1997-07-01
影响因子：
4.3
通讯作者：
Thomas, DW
中科院分区：
文献类型：
--
作者：
Chen, YQ;Nixon, MS;Thomas, DW
纹理分析在遥感、医学诊断和质量控制等领域有着广泛的应用。对图像纹理进行分类的方法有很多种，并且许多方法将问题分解为提取和分类。我们描述了使用新的统计几何特征的特征提取，并与刘的特征、使用几何区域的傅里叶变换的特征、统计灰度级依赖矩阵和统计特征矩阵进行比较。我们还在统计几何特征中包含了有关旋转不变性的正式分析。这里考虑的分类技术包括 K 最近邻规则、误差机架传播方法和新的生成收缩算法。一个特别的考虑因素是特征空间中的尺度不变性，因为这意味着即使整体照明水平不同，纹理也可以被分类为相同的。对整个 Brodatz 纹理集的实验评估表明，统计几何特征可以为所有考虑的分类器提供最佳性能，生成收缩算法可以提供比 Err 或反向传播方法更好的性能，并且 K 最近邻规则的性能与生成收缩算法相当。此外，统计几何特征与生成收缩算法的组合构成了所考虑的最佳纹理分类系统之一。
Texture analysis has found wide application in, say, remote sensing, medical diagnosis, and quality control. There are many ways to classify image texture and many approaches split the problem into extraction followed by classification. We describe feature extraction using the new Statistical Geometrical Features in comparison with Liu's features, features from the Fourier transform using geometrical regions, the Statistical Grey Level Dependency Matrix and the Statistical Feature Matrix. We also include a formal analysis concerning rotational-invariance in the Statistical Geometric Features. Classification techniques considered here include the K-Nearest Neighbour Rule, the Error Rack-propagation method and the new Generating-Shrinking Algorithm. A particular consideration is scale-invariance in the feature space since this implies that textures can be classified as the same, even when the overall illumination level differs. Experimental evaluation on the whole Brodatz texture set shows that the Statistical Geometrical Features can give the best performance for all the considered classifiers, that the Generating-Shrinking Algorithm can offer better performance over the Err or Back-Propagation method and that the K-Nearest Neighbour Rule's performance is comparable with that of the Generating-Shrinking Algorithm. Also, the combination of the Statistical Geometrical Features with the Generating-Shrinking Algorithm constitutes one of the best texture classification systems considered.