{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:26:00Z","timestamp":1750220760941,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":10,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,11,13]],"date-time":"2019-11-13T00:00:00Z","timestamp":1573603200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Beihua University","award":["Graduate Innovation Program of Beihua University [2019](050)"],"award-info":[{"award-number":["Graduate Innovation Program of Beihua University [2019](050)"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,11,13]]},"DOI":"10.1145\/3379299.3379304","type":"proceedings-article","created":{"date-parts":[[2020,3,20]],"date-time":"2020-03-20T20:36:50Z","timestamp":1584736610000},"page":"22-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["An Image Segmentation Method Based on Peak-valley Principle and K-means Algorithm"],"prefix":"10.1145","author":[{"given":"Wenjie","family":"Yao","sequence":"first","affiliation":[{"name":"School of computer science and technology, Beihua University, Jilin City, Jilin Province, China"}]},{"given":"Taihui","family":"Liu","sequence":"additional","affiliation":[{"name":"School of computer science and technology, Beihua University, Jilin City, Jilin Province, China"}]}],"member":"320","published-online":{"date-parts":[[2020,3,20]]},"reference":[{"issue":"04","key":"e_1_3_2_1_1_1","first-page":"170","article-title":"Improvement of K-means clustering algorithm for bee colony [J].","volume":"32","author":"Yuehua Hong","year":"2016","unstructured":"Hong Yuehua . Improvement of K-means clustering algorithm for bee colony [J]. Science and Technology Bulletin , 2016 , 32 ( 04 ): 170 -- 173 . Hong Yuehua. Improvement of K-means clustering algorithm for bee colony [J].Science and Technology Bulletin, 2016, 32(04): 170--173.","journal-title":"Science and Technology Bulletin"},{"issue":"05","key":"e_1_3_2_1_2_1","first-page":"422","article-title":"K-means clustering algorithm based on searcher optimization algorithm [J]","volume":"42","author":"Shenghui Wang","year":"2018","unstructured":"Wang Shenghui , Xia Yongfeng . K-means clustering algorithm based on searcher optimization algorithm [J] . Journal of Yanshan University , 2018 , 42 ( 05 ): 422 -- 426 + 433. Wang Shenghui, Xia Yongfeng. K-means clustering algorithm based on searcher optimization algorithm [J]. Journal of Yanshan University, 2018, 42 (05): 422--426 + 433.","journal-title":"Journal of Yanshan University"},{"key":"e_1_3_2_1_3_1","volume-title":"K-means clustering algorithm based on adaptive cuckoo search algorithm and its application [J]. Computer applications","author":"Huihua Yang","year":"2016","unstructured":"Yang Huihua , Wang Ke , Li Mingqiao , Wei Wen , He Shengtao . K-means clustering algorithm based on adaptive cuckoo search algorithm and its application [J]. Computer applications , 2016 , 36 (08): 2066--2070. Yang Huihua, Wang Ke, Li Mingqiao, Wei Wen, He Shengtao. K-means clustering algorithm based on adaptive cuckoo search algorithm and its application [J]. Computer applications, 2016, 36 (08): 2066--2070."},{"key":"e_1_3_2_1_4_1","volume-title":"Li Bolin. Image segmentation based on random weight particle swarm and K-means clustering [J]. Journal of graphics","author":"Haiyang Li","year":"2014","unstructured":"Li Haiyang , Wen Yongge , he Hongzhou , Li Bolin. Image segmentation based on random weight particle swarm and K-means clustering [J]. Journal of graphics , 2014 , 35 (05): 755--761. Li Haiyang, Wen Yongge, he Hongzhou, Li Bolin. Image segmentation based on random weight particle swarm and K-means clustering [J]. Journal of graphics, 2014, 35 (05): 755--761."},{"key":"e_1_3_2_1_5_1","volume-title":"Image segmentation algorithm based on dynamic particle swarm optimization and K-means clustering [J]. Modern electronic technology","author":"Lijun Li","year":"2018","unstructured":"Li Lijun , Zhang Xiaoguang . Image segmentation algorithm based on dynamic particle swarm optimization and K-means clustering [J]. Modern electronic technology , 2018 , 41 (10): 164--168. Li Lijun, Zhang Xiaoguang. Image segmentation algorithm based on dynamic particle swarm optimization and K-means clustering [J]. Modern electronic technology, 2018, 41 (10): 164--168."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2011.12.009"},{"issue":"06","key":"e_1_3_2_1_7_1","first-page":"1164","article-title":"Research on K-means clustering segmentation method of brain tissue MRI image based on gray histogram multi peak selection [J]","volume":"30","author":"Zhaoxue Chen","year":"2013","unstructured":"Chen Zhaoxue , Yu Haizhong , Chen Hao . Research on K-means clustering segmentation method of brain tissue MRI image based on gray histogram multi peak selection [J] . Journal of Biomedical Engineering , 2013 , 30 ( 06 ): 1164 -- 1170 Chen Zhaoxue, Yu Haizhong, Chen Hao. Research on K-means clustering segmentation method of brain tissue MRI image based on gray histogram multi peak selection [J]. Journal of Biomedical Engineering, 2013, 30 (06): 1164--1170","journal-title":"Journal of Biomedical Engineering"},{"key":"e_1_3_2_1_8_1","volume-title":"Bone scanning image segmentation based on kernel density estimation and K-means clustering algorithm [J]","author":"Lei Xu","year":"2015","unstructured":"Xu Lei , Meng Qingle , Yang Rui , Cao Yan , Wang Feng , Cui Guang , Jiang Hongbing . Bone scanning image segmentation based on kernel density estimation and K-means clustering algorithm [J] . Journal of Nanjing Medical University (Natural Science Edition) , 2015 , 35 (04): 585--589. Xu Lei, Meng Qingle, Yang Rui, Cao Yan, Wang Feng, Cui Guang, Jiang Hongbing. Bone scanning image segmentation based on kernel density estimation and K-means clustering algorithm [J]. Journal of Nanjing Medical University (Natural Science Edition), 2015, 35 (04): 585--589."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2006.03.009"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/0377-0427(87)90125-7"}],"event":{"name":"DMIP '19: 2019 2nd International Conference on Digital Medicine and Image Processing","sponsor":["East China Normal University","University of Tsukuba University of Tsukuba"],"location":"Shanghai China","acronym":"DMIP '19"},"container-title":["Proceedings of the 2019 2nd International Conference on Digital Medicine and Image Processing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3379299.3379304","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3379299.3379304","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:41:02Z","timestamp":1750200062000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3379299.3379304"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,13]]},"references-count":10,"alternative-id":["10.1145\/3379299.3379304","10.1145\/3379299"],"URL":"https:\/\/doi.org\/10.1145\/3379299.3379304","relation":{},"subject":[],"published":{"date-parts":[[2019,11,13]]},"assertion":[{"value":"2020-03-20","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}