基于主动轮廓模型的沉香显微图像特征提取算法研究
首发时间:2016-12-02
摘要:为了对沉香进行分类识别,提出一种基于沉香显微图像的木纤维分割及特征提取方法。使用主动轮廓模型对沉香显微图像进行轮廓提取,木纤维筛选后,对其几何特征和形状因子等特征进行提取,组成特征向量,并应用支持向量机实现两种实验沉香图像分类,实验结果表明:提出的特征能够很好的表示沉香木纤维,分类算法实现简单,具有良好的分类性能。
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Research on Feature Extraction Method for Eaglewood Image Based on Active Contour Model
Abstract:In order to classify the eaglewood, the work proposed a method of wood fiber segmentation and characteristic extraction based on the eaglewood micrographs. The active contour model was used to extract the contours of the eaglewood micrographs. After screening of wood fiber, the geometric features and shape factors were extracted to form characteristic vectors. After that, SVM was used to achieve the classification of the two kinds of eaglewood micrographs. Results show that the extracted characteristics can be used to express eaglewood fiber. With good classification performance, classification algorithm is easy to achieve.
Keywords: Machine vision Active contour model Microscopic feature Detection of eaglewood
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No.4711649880507148****
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