Tsuyoshi Shimizu, Yasutake Haramiishi, Y. A. Rahim, Syamir Alihan, Yuji Kobayashi, A. Matsui, Shinji Kotani, H. Watanabe
{"title":"喷丸强化加工表面的图像评价","authors":"Tsuyoshi Shimizu, Yasutake Haramiishi, Y. A. Rahim, Syamir Alihan, Yuji Kobayashi, A. Matsui, Shinji Kotani, H. Watanabe","doi":"10.1117/12.2585193","DOIUrl":null,"url":null,"abstract":"This paper describes an evaluation method of shot peened surface using image processing. Shot peening is a process that applies compressive residual stress to the product surface, and its evaluation is performed visually by an expert. If visual inspection can be replaced with image processing, the inspection of the entire product will be easier. Therefore, first reference samples that experts evaluate are prepared, next these samples are evaluated by image processing. relationship between expert evaluations and image processing evaluations are compared and the estimation function is defined using gausian distribution. Unknown processed surfaces are evaluated as a classification problem. For image processing, after binarization and labeling, the number of labels and the area ratio of binarization are used.","PeriodicalId":295011,"journal":{"name":"International Conference on Quality Control by Artificial Vision","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluation of shot peening machined surface by image processing\",\"authors\":\"Tsuyoshi Shimizu, Yasutake Haramiishi, Y. A. Rahim, Syamir Alihan, Yuji Kobayashi, A. Matsui, Shinji Kotani, H. Watanabe\",\"doi\":\"10.1117/12.2585193\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes an evaluation method of shot peened surface using image processing. Shot peening is a process that applies compressive residual stress to the product surface, and its evaluation is performed visually by an expert. If visual inspection can be replaced with image processing, the inspection of the entire product will be easier. Therefore, first reference samples that experts evaluate are prepared, next these samples are evaluated by image processing. relationship between expert evaluations and image processing evaluations are compared and the estimation function is defined using gausian distribution. Unknown processed surfaces are evaluated as a classification problem. For image processing, after binarization and labeling, the number of labels and the area ratio of binarization are used.\",\"PeriodicalId\":295011,\"journal\":{\"name\":\"International Conference on Quality Control by Artificial Vision\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Quality Control by Artificial Vision\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2585193\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Quality Control by Artificial Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2585193","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Evaluation of shot peening machined surface by image processing
This paper describes an evaluation method of shot peened surface using image processing. Shot peening is a process that applies compressive residual stress to the product surface, and its evaluation is performed visually by an expert. If visual inspection can be replaced with image processing, the inspection of the entire product will be easier. Therefore, first reference samples that experts evaluate are prepared, next these samples are evaluated by image processing. relationship between expert evaluations and image processing evaluations are compared and the estimation function is defined using gausian distribution. Unknown processed surfaces are evaluated as a classification problem. For image processing, after binarization and labeling, the number of labels and the area ratio of binarization are used.