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On-Tree Detection and Counting of Apple Using Color Thresholding and CHT

机译:使用颜色阈值和CHT对苹果进行树上检测和计数

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One of the challenges in continual fruit cultivation is to approximately calculate the number of fruits on a tree. This helps to get yield estimation for different farm operation. On-tree detection and counting of apple fruits in a correct manner is a challenging task in computer vision. This work implements circular Hough transform (CHT) and colour thresholding in an iterative manner in image processing method to detect and count each apple fruit. The fruit identified by CHT which were clearly visible are preferred for early harvesting than the partially visible fruits. The methodology proposed in this paper has the capability to detect and count fully visible as well as partially visible apple fruit. The precedence of Circular Hough Transform is to detect and count overlapping fruit. The count evaluated by the proposed algorithm results in 97.70% of accuracy.
机译:持续进行水果种植的挑战之一是大约计算一棵树上的水果数量。这有助于获得针对不同农场运营的收益估算。在树上检测和正确计数苹果果实是计算机视觉中的一项艰巨任务。这项工作在图像处理方法中以迭代方式实现了循环霍夫变换(CHT)和颜色阈值处理,以检测和计数每个苹果果实。通过CHT识别的清晰可见的果实比部分可见的果实更适合早期收获。本文提出的方法具有检测和计数完全可见以及部分可见的苹果果实的能力。环形霍夫变换的优先级是检测和计数重叠的水果。提出的算法评估的计数结果达到了97.70%的准确性。

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