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A comparative approach for image segmentation to identify the defected portion of apple

机译:图像分割识别苹果缺陷部分的比较方法

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A crucially significant process for the automatic fruit grading system is image segmentation. The area of interest is extracted by separating the image into several areas. Intensity of the object color surface varies with the illumination. The external fruit properties namely shape, size, texture and color, give base to various fruit quality detection technique. As it is very difficult to sort out the good quality fruits, so the aim of machine based system is to replace manual techniques. With a large demand of fruits the ineffective manual monitoring poses a problem. Various methods such as Otsu, k-means, fuzzy c-means and watershed segmentation are used for image segmentation. Speeded up robust technique estimate the local features. Implementation of all segmentation methods on fruit images is applied and a comparative research outcome is projected to find the defected portion of fruits.
机译:自动水果分级系统的一个至关重要的重要过程是图像分割。通过将图像分成几个区域来提取感兴趣的区域。物体颜色表面的强度随照明而变化。外部水果的属性,即形状,大小,质地和颜色,为各种水果质量检测技术奠定了基础。由于很难挑选出高质量的水果,因此基于机器的系统的目的是取代手工技术。由于水果需求量很大,无效的手动监控带来了问题。使用大津,k均值,模糊c均值和分水岭分割等各种方法进行图像分割。加快鲁棒性技术估计局部特征。应用在水果图像上所有分割方法的实现,并计划进行比较研究,以发现水果的缺陷部分。

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