Automatic Produce Classification from Images Using Color, Texture and Appearance Cues

A. Rocha, D. C. Hauagge, Jacques Wainer, S. Goldenstein
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引用次数: 24

Abstract

We propose a system to solve a multi-class produce categorization problem. For that, we use statistical color, texture, and structural appearance descriptors (bag-of-features). As the best combination setup is not known for our problem, we combine several individual features from the state-of-the-art in many different ways to assess how they interact to improve the overall accuracy of the system. We validate the system using an image data set collected on our local fruits and vegetables distribution center.
自动产生分类从图像使用颜色,纹理和外观线索
提出了一个解决多类农产品分类问题的系统。为此,我们使用统计颜色、纹理和结构外观描述符(特征袋)。由于我们的问题不知道最佳组合设置,我们以许多不同的方式组合来自最先进的几个单独的特征,以评估它们如何相互作用以提高系统的整体准确性。我们使用在当地水果和蔬菜配送中心收集的图像数据集验证了该系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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