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Determination of Mango Fruit from Binary Image Using Randomized Hough Transform

机译:采用随机霍夫变换的二值图像测定芒果果实

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A method of detecting mango fruit from RGB input image is proposed in this research. From the input image, the image is processed to obtain the binary image using the texture analysis and morphological operations (dilation and erosion). Later, the Randomized Hough Transform (RHT) method is used to find the best ellipse fits to each binary region. By using the texture analysis, the system can detect the mango fruit that is partially overlapped with each other and mango fruit that is partially occluded by the leaves. The combination of texture analysis and morphological operator can isolate the partially overlapped fruit and fruit that are partially occluded by leaves. The parameters derived from RHT method was used to calculate the center of the ellipse. The center of the ellipse acts as the gripping point for the fruit picking robot. As the results, the rate of detection was up to 95% for fruit that is partially overlapped and partially covered by leaves.
机译:在该研究中提出了一种检测RGB输入图像的芒果果实的方法。根据输入图像,处理图像以使用纹理分析和形态操作(扩张和侵蚀)获得二进制图像。后来,随机霍夫变换(RHT)方法用于找到每个二进制区域的最佳椭圆。通过使用纹理分析,系统可以检测芒果果实,该果实彼此部分地重叠,芒果果实被叶子部分封闭。纹理分析和形态算子的组合可以分离部分重叠的果实和叶子部分封闭的果实。源自RHT方法的参数用于计算椭圆的中心。椭圆的中心充当水果采摘机器人的抓握点。结果,果实的检测速率高达95%,叶子部分重叠并部分地被叶子覆盖。

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