{"title":"基于图像分割算法的两种碳酸盐岩鲕粒提取方法","authors":"Yili Ren, Jian Liang, Siwu Luo","doi":"10.1109/ICISCAE52414.2021.9590702","DOIUrl":null,"url":null,"abstract":"Carbonate rock is a kind of very valuable sedimentary rock, and oolites are one of the most easily identifiable particles in the carbonate rock image. Based on the traditional image segmentation algorithm, this paper proposes two extraction strategies for carbonate oolitic components. The first is the extraction technology of carbonate rock oolites based on traditional image segmentation algorithm: first extract the connected domains of the carbonate rock image, then use the K-Means clustering algorithm to analyze the processed image, and then analyze the image Binary processing, and finally extract the contours of the oolites; the second, the carbonate rock oolite extraction technology based on the superpixel segmentation algorithm: first use the SLIC algorithm to segment the acid rock image; secondly, the road extract. The test results show that the two extraction strategies can clearly extract the oolitic components of salt rock. In addition, according to the experimental results in this paper, it can be seen that the oolitic extraction technology based on SLIC superpixel segmentation is slightly better than that based on traditional image segmentation algorithm.","PeriodicalId":121049,"journal":{"name":"2021 IEEE 4th International Conference on Information Systems and Computer Aided Education (ICISCAE)","volume":"89 11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Two extraction methods for carbonate rock oolites based on image segmentation algorithm\",\"authors\":\"Yili Ren, Jian Liang, Siwu Luo\",\"doi\":\"10.1109/ICISCAE52414.2021.9590702\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Carbonate rock is a kind of very valuable sedimentary rock, and oolites are one of the most easily identifiable particles in the carbonate rock image. Based on the traditional image segmentation algorithm, this paper proposes two extraction strategies for carbonate oolitic components. The first is the extraction technology of carbonate rock oolites based on traditional image segmentation algorithm: first extract the connected domains of the carbonate rock image, then use the K-Means clustering algorithm to analyze the processed image, and then analyze the image Binary processing, and finally extract the contours of the oolites; the second, the carbonate rock oolite extraction technology based on the superpixel segmentation algorithm: first use the SLIC algorithm to segment the acid rock image; secondly, the road extract. The test results show that the two extraction strategies can clearly extract the oolitic components of salt rock. In addition, according to the experimental results in this paper, it can be seen that the oolitic extraction technology based on SLIC superpixel segmentation is slightly better than that based on traditional image segmentation algorithm.\",\"PeriodicalId\":121049,\"journal\":{\"name\":\"2021 IEEE 4th International Conference on Information Systems and Computer Aided Education (ICISCAE)\",\"volume\":\"89 11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 4th International Conference on Information Systems and Computer Aided Education (ICISCAE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICISCAE52414.2021.9590702\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 4th International Conference on Information Systems and Computer Aided Education (ICISCAE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICISCAE52414.2021.9590702","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Two extraction methods for carbonate rock oolites based on image segmentation algorithm
Carbonate rock is a kind of very valuable sedimentary rock, and oolites are one of the most easily identifiable particles in the carbonate rock image. Based on the traditional image segmentation algorithm, this paper proposes two extraction strategies for carbonate oolitic components. The first is the extraction technology of carbonate rock oolites based on traditional image segmentation algorithm: first extract the connected domains of the carbonate rock image, then use the K-Means clustering algorithm to analyze the processed image, and then analyze the image Binary processing, and finally extract the contours of the oolites; the second, the carbonate rock oolite extraction technology based on the superpixel segmentation algorithm: first use the SLIC algorithm to segment the acid rock image; secondly, the road extract. The test results show that the two extraction strategies can clearly extract the oolitic components of salt rock. In addition, according to the experimental results in this paper, it can be seen that the oolitic extraction technology based on SLIC superpixel segmentation is slightly better than that based on traditional image segmentation algorithm.