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首页> 外文会议>Optics in Agriculture and Forestry >Machine recognition of weevil damage in wheat radiographs
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Machine recognition of weevil damage in wheat radiographs

机译：小麦射线照相中象鼻虫危害的机器识别

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Abstract: e processing algorithm has been developed for machine recognition of weevils and/or weevil damage in film x-ray images of wheat kernels $LB@8 bits, (0.25 mm)$+2$//pixel$RB@. The 8 bit grey scale image is converted to a binary image of interior edges and lines using a Laplacian mask, zero threshold, and background removal. In undamaged kernels the predominant feature of this image is a line representing the central crease of the kernel. In insect-damaged kernels this feature is disrupted and additional edges or lines are seen at angles to the crease. The algorithm uses convolution masks to look for intersections (45 or 90 degree angles with 4 or 5 pixel length sides) at 8 orientations. Recognition varies with insect stage; at least 50% of infested kernels are machine recognized by the 4th instar (26 - 28 days). This is comparable to 50% recognition by humans at 25.5 days for images of similar resolution. False positive responses are limited to 0.5%. !27
机译：摘要：已经开发出一种处理算法，用于机器识别小麦粒$ LB @ 8位（0.25 mm）$ + 2 $ // pixel $ RB @的胶片X射线图像中的象鼻虫和/或象鼻虫损害。使用拉普拉斯遮罩，零阈值和背景去除，将8位灰度图像转换为内部边缘和线条的二进制图像。在未损坏的内核中，此图像的主要特征是代表内核中央折痕的线。在虫害内核中，此特征被破坏，并且在折痕的角度处看到了其他边缘或线条。该算法使用卷积遮罩在8个方向上查找相交（45或90度角，带有4或5个像素长度的边）。识别因昆虫阶段而异。至少有50％的受感染内核被第四龄（26-28天）机器识别。对于类似分辨率的图像，这相当于人类在25.5天时50％的识别率。假阳性反应限于0.5％。 ！27

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