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A novel method for recognizing fruits with plastic packing

机译:塑料包装识别水果的新方法

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According to the need of automatic weighing and pricing system for fruits in the supermarket and the limitation of current methods, this paper proposes a new segmentation method for fruits with plastic packing and a modified minimum distance classifier. Firstly, we segment images and obtain the region of interest (ROI) in the HSV color space. Secondly, we extract color features and texture features which can be derived from gray level co-occurrence matrix (GLCM), and saving these features into the classifier. Then, we apply modified classifier to recognize and categorize. The experiment results show that our segmentation method can separate ROI from the background with plastic packaging effectively. Furthermore, this novel method can also achieve a better recognition performance with overall recognition rate above 91%.
机译:针对超市水果自动称重和定价系统的需求,结合目前方法的局限性,提出了一种采用塑料包装和改进的最小距离分类器的水果细分方法。首先,我们分割图像并获得HSV颜色空间中的关注区域(ROI)。其次,我们提取可以从灰度共生矩阵(GLCM)派生的颜色特征和纹理特征,并将这些特征保存到分类器中。然后,我们应用修改后的分类器进行识别和分类。实验结果表明,采用塑料包装分割方法可以有效地将ROI与背景分离。此外,该新方法还可以实现更好的识别性能,总体识别率达到91%以上。

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