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Determination of Mango Fruit from Binary Image Using Randomized Hough Transform

机译:利用随机霍夫变换从二值图像确定芒果果

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摘要

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:提出了一种从RGB输入图像中检测芒果果实的方法。使用纹理分析和形态学运算(膨胀和腐蚀),从输入图像中对图像进行处理以获得二进制图像。后来,使用了随机霍夫变换(RHT)方法来找到每个二进制区域的最佳椭圆拟合。通过使用纹理分析,系统可以检测到彼此部分重叠的芒果果实和部分被叶子遮挡的芒果果实。纹理分析和形态算子的结合可以分离出部分重叠的水果和部分被叶子遮挡的水果。从RHT方法导出的参数用于计算椭圆的中心。椭圆的中心是采摘机器人的抓点。结果,部分重叠和部分被叶子覆盖的水果的检出率高达95%。

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