改进的主动形状模型在植物叶形分类中的应用

Advanced Active Shape Model Applications of Classifying Plant Leaves

针对植物叶形识别的特点,采用改进的主动形状模型实现叶片图像的批量识别和分类。在模型中以地标点序列表示对象形状轮廓,分别应用覆盖面积半径和生物学参照点进行伸缩变换和旋转变换,归一化地标点序列间的统计关系,进而研究形状间的相似性和差异性;在分类时通过设置相似度阈值,强化了同类叶片的标准,从而减少了一些非同类的误归入事件的发生。实验表明改进的主动形状模型在叶形识别中得到稳健的识别率。

The characteristics of plant leaf used to identify initiatives to improve the shape of the model leaves the bulk image identification and classification. In the model, and punctuation sequence that forms the outline of the object, namely the application of the coverage area of the radius and biological reference points for telescopic transformation and rotation transformation, normalized to punctuation sequence statistical relationship between the shape of further study similarities and differences. In the classification by setting the similarity threshold, the stand- ards is strengthened of similar leaves, thereby reducing the number of wrongly classified as non-similar incidents. Experiments show that the initiative to improve the shape model in shape recognition rate has been steady~