{"title":"基于图像处理的硬度压痕检测与分类技术","authors":"A. C. Shilin, B. Wei","doi":"10.1109/RCAR54675.2022.9872294","DOIUrl":null,"url":null,"abstract":"Hardness measurement methods are simple, effective and convenient, and have great practical value. In order to improve the efficiency of hardness detection to adapt to product requirements, automated detection requirements are put forward for hardness indentation detection.Based on image processing, this paper studies the detection and classification technology of hardness indentation, and accomplishes the following research work: identifying the surface condition of hardness block and planning the new indentation trajectory based on the recognition results; Based on deep learning, an indentation classification algorithm is designed to improve the sorting accuracy and speed of hardness blocks. The research results can be used in engineering applications.Through theoretical analysis and experimental verification, the hardness indentation detection and classification technology based on image processing has high positioning, classification and detection speed and accuracy, which meets the automation requirements of hardness detection.","PeriodicalId":304963,"journal":{"name":"2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hardness indentation detection and classification technology based on image processing\",\"authors\":\"A. C. Shilin, B. Wei\",\"doi\":\"10.1109/RCAR54675.2022.9872294\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Hardness measurement methods are simple, effective and convenient, and have great practical value. In order to improve the efficiency of hardness detection to adapt to product requirements, automated detection requirements are put forward for hardness indentation detection.Based on image processing, this paper studies the detection and classification technology of hardness indentation, and accomplishes the following research work: identifying the surface condition of hardness block and planning the new indentation trajectory based on the recognition results; Based on deep learning, an indentation classification algorithm is designed to improve the sorting accuracy and speed of hardness blocks. The research results can be used in engineering applications.Through theoretical analysis and experimental verification, the hardness indentation detection and classification technology based on image processing has high positioning, classification and detection speed and accuracy, which meets the automation requirements of hardness detection.\",\"PeriodicalId\":304963,\"journal\":{\"name\":\"2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RCAR54675.2022.9872294\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RCAR54675.2022.9872294","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hardness indentation detection and classification technology based on image processing
Hardness measurement methods are simple, effective and convenient, and have great practical value. In order to improve the efficiency of hardness detection to adapt to product requirements, automated detection requirements are put forward for hardness indentation detection.Based on image processing, this paper studies the detection and classification technology of hardness indentation, and accomplishes the following research work: identifying the surface condition of hardness block and planning the new indentation trajectory based on the recognition results; Based on deep learning, an indentation classification algorithm is designed to improve the sorting accuracy and speed of hardness blocks. The research results can be used in engineering applications.Through theoretical analysis and experimental verification, the hardness indentation detection and classification technology based on image processing has high positioning, classification and detection speed and accuracy, which meets the automation requirements of hardness detection.
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