适用于可扩展移动应用程序的图像处理和分类方法

N. Petrellis
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引用次数: 0

摘要

本文描述的图像处理技术可用于显示感兴趣对象的照片的分类。物体上被潜在光晕包围的具有不同颜色的点被分割。灰度、面积和斑点的数量可以决定照片中显示的物体的类别。在属于同一类别的不同照片中,感兴趣区域的颜色直方图预计具有相似的形式。该算法不采用复杂的模式匹配算法,而是采用简单的特征,包括叶的位置和峰值。植物或皮肤疾病诊断是指示性应用,可以从所提出的方法中受益。在采用所提出的方法的情况下,实现了高速分类和良好的准确性。然而,它们的主要优点是简单性,允许扩展,因为在对少量照片进行初步统计处理后就可以支持新的类。
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Image Processing and Classification Method Appropriate for Extensible Mobile Applications
The image processing technique described in this paper can be used for the classification of photographs that display an object of interest. Spots on the object having distinct color surrounded by a potential halo are segmented. The gray level, area and the number of the spots can determine the class of the object displayed in the photograph. The color histograms of the regions of interest are expected to have similar form in different photographs belonging to the same class. Instead of employing complicated pattern matching algorithms simple features are used including the position and the peaks of the lobes. Plant or skin disease diagnosis are indicative applications that can benefit from the proposed method. High speed classification is achieved with good accuracy in the cases where the proposed methods have been employed. However, their main advantage is the simplicity that allows extensibility since new classes can be supported after a draft statistical processing of a small number of photographs.
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