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Classification of color objects like fruits using probability density function (PDF)

机译:使用概率密度函数对水果等有色物体进行分类(PDF)

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摘要

Fruits like apples are valued based on their appearance (i.e. color, sizes, shapes, presence of surface defects) and hence classified into different grades. Grading process helps in achieving better standards and quality of fruits. Of the many available color models, HSI model provides a highly effective color evaluation particularly for analyzing biological products. Human assessment furnishes only qualitative data and such inspection is time consuming and cost-intensive. Machine vision systems with specialized image processing software provide a solution that may satisfy the demand. The analysis was carried out on images of 187 apple fruits, shows that classification done based on median of PDF. In order to avoid the mismatch in grading the same it has been classified further using Histogram Intersection, which determines the closeness between two images i.e. 1 if two images are similar and 0 if they are dissimilar.
机译:苹果等水果是根据其外观(即颜色,大小,形状,表面缺陷的存在)进行估价的,因此分为不同等级。分级过程有助于达到更好的水果标准和质量。在许多可用的颜色模型中,HSI模型可提供高效的颜色评估,特别是用于分析生物产品。人工评估仅提供定性数据,而这种检查既费时又费钱。具有专用图像处理软件的机器视觉系统提供了可以满足需求的解决方案。对187个苹果果实的图像进行了分析,结果表明分类基于PDF的中位数。为了避免分级时的不匹配,已使用直方图相交对其进行了进一步分类,直方图相交确定了两个图像之间的紧密度,即,如果两个图像相似,则为1;如果两个图像不同,则为0。

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