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首页> 外文期刊>Optik: Zeitschrift fur Licht- und Elektronenoptik: = Journal for Light-and Electronoptic >Detecting citrus fruits with highlight on tree based on fusion of multi-map
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Detecting citrus fruits with highlight on tree based on fusion of multi-map

机译:基于多图融合的树上高亮柑橘类水果检测

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摘要

Artificial vision systems are powerful tools for the automatic guiding of fruit harvesting robots, a novel method based on chromatic aberration map and luminance map is developed to identify citrus fruits with highlight within a tree canopy. Twenty images of citrus-grove scene under direct sunlight are taken, the color properties of target objects are analyzed. First, parts of citrus fruits from background are segmented from background by thresholding the CAM (chromatic aberration map), then the highlight region of citrus fruits could be detected correctly from the tree canopy by thresholding the LM (luminance map), at last the citrus fruits can be detected integrally by fusing the segmented results of CAM and LM. The results showed that the fruits under direct sunlight can be segmented wholly using this algorithm, the detection accuracy by fusion method is up to 86.81%, and the false alarm rate of fusion method is 2.25%.
机译:人工视觉系统是自动引导水果收获机器人的强大工具,基于色差图和亮度图的新方法被开发出来,用于识别树冠内有突出显示的柑橘类水果。拍摄了20幅阳光直射下的柑橘林场景的图像,分析了目标物体的色彩特性。首先,通过对CAM(色差图)进行阈值化,将背景中的柑橘类水果从背景中分割出来,然后通过对LM(亮度图)进行阈值化,可以从树冠中正确地检测出柑橘类水果的高光区域,最后将柑橘类水果通过融合CAM和LM的分段结果,可以整体检测水果。结果表明,该算法可以对阳光直射下的水果进行整体分割,融合方法的检测准确率高达86.81%,融合方法的误报率为2.25%。

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