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Detection of insect damage in almonds

机译:检测杏仁中的昆虫危害

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摘要

Abstract: Pinhole insect damage in natural almonds is very difficult to detect on-line. Further, evidence exists relating insect damage to aflatoxin contamination. Hence, for quality and health reasons, methods to detect and remove such damaged nuts are of great importance in this study, we explored the possibility of using x-ray imaging to detect pinhole damage in almonds by insects. X-ray film images of about 2000 almonds and x-ray linescan images of only 522 pinhole damaged almonds were obtained. The pinhole damaged region appeared slightly darker than non-damaged region in x-ray negative images. A machine recognition algorithm was developed to detect these darker regions. The algorithm used the first order and the second order information to identify the damaged region. To reduce the possibility of false positive results due to germ region in high resolution images, germ detection and removal routines were also included. With film images, the algorithm showed approximately an 81 percent correct recognition ratio with only 1 percent false positives whereas line scan images correctly recognized 65 percent of pinholes with about 9 percent false positives. The algorithms was very fast and efficient requiring only minimal computation time. If implemented on line, theoretical throughput of this recognition system would be 66 nuts/second. !11
机译:摘要:天然杏仁中的针孔虫害很难在线检测。此外,存在将昆虫损害与黄曲霉毒素污染相关的证据。因此,出于质量和健康的原因,检测和去除此类受损坚果的方法在本研究中非常重要,我们探索了使用X射线成像检测昆虫对杏仁造成的针孔损害的可能性。获得了大约2000个杏仁的X射线胶片图像和仅522个针孔损坏的杏仁的X射线线扫描图像。在X射线负像中,针孔损坏的区域看上去比未损坏的区域稍暗。开发了一种机器识别算法来检测这些较暗的区域。该算法使用一阶和二阶信息来识别损坏区域。为了减少高分辨率图像中由于细菌区域而导致假阳性结果的可能性,还包括细菌检测和清除程序。对于胶片图像,该算法显示出大约81%的正确识别率,只有1%的误报,而线扫描图像则正确地识别了65%的针孔,大约有9%的误报。该算法非常快速和高效,仅需要最少的计算时间。如果在线实施,则该识别系统的理论吞吐量将为66个坚果/秒。 !11

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