{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T06:24:25Z","timestamp":1743143065432,"version":"3.40.3"},"publisher-location":"Cham","reference-count":10,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031044083"},{"type":"electronic","value":"9783031044090"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-04409-0_24","type":"book-chapter","created":{"date-parts":[[2022,5,17]],"date-time":"2022-05-17T09:10:13Z","timestamp":1652778613000},"page":"254-269","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Image Retrieval Algorithm Based on Fractal Coding"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2126-9757","authenticated-orcid":false,"given":"Hui","family":"Guo","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1210-3504","authenticated-orcid":false,"given":"Jie","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4296-0192","authenticated-orcid":false,"given":"Caixu","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6217-7248","authenticated-orcid":false,"given":"Dongling","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,5,18]]},"reference":[{"issue":"5","key":"24_CR1","first-page":"5","volume":"9","author":"AD Sloan","year":"1994","unstructured":"Sloan, A.D.: Retrieving database contents by image recognition: new fractal power. Adv. Imaging 9(5), 5\u201315 (1994)","journal-title":"Adv. Imaging"},{"issue":"8","key":"24_CR2","first-page":"310","volume":"46","author":"J-J Zhang","year":"2019","unstructured":"Zhang, J.-J., Zhang, A.-H., Ji, H.-F.: Image compression encoding based on wavelet transform and fractal. Comput. Sci. 46(8), 310\u2013314 (2019)","journal-title":"Comput. Sci."},{"doi-asserted-by":"crossref","unstructured":"Prashanth, N., Arun, V.S.: Fractal image compression for HD image with noise using wavelet transforms. In: 2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI), New York, pp. 1194\u20131198. IEEE Press (2015)","key":"24_CR3","DOI":"10.1109\/ICACCI.2015.7275774"},{"unstructured":"Pang, H., Zhang, A.: Sparse coding algorithm for fractal image compression based on coefficient of variation. Appl. Res. Comput. 38(7) (2020)","key":"24_CR4"},{"issue":"3","key":"24_CR5","first-page":"284","volume":"38","author":"Q Zhang","year":"2017","unstructured":"Zhang, Q., Lin, Q.-H., Kang, X.: Research on image retrieval based on kernel density estimation and fractal coding algorithm. Acta Metrologica Sin. 38(3), 284\u2013287 (2017)","journal-title":"Acta Metrologica Sin."},{"issue":"12","key":"24_CR6","first-page":"292","volume":"42","author":"S-S Zhang","year":"2015","unstructured":"Zhang, S.-S., Liu, Y., Zhao, Z.-B.: Fractal image retrieval algorithm based on contiguous-matches. Comput. Sci. 42(12), 292\u2013296 (2015)","journal-title":"Comput. Sci."},{"issue":"2","key":"24_CR7","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1504\/IJSPM.2020.106975","volume":"15","author":"H Yuan","year":"2020","unstructured":"Yuan, H., Li, M., Niu, W., Zhang, L., Cui, K.: Fast fractal image retrieval algorithm based on HV partition. Int. J. Simul. Process Model. 15(2), 111\u2013118 (2020)","journal-title":"Int. J. Simul. Process Model."},{"issue":"1","key":"24_CR8","first-page":"215","volume":"13","author":"MF Barnsley","year":"1988","unstructured":"Barnsley, M.F., Sloan, A.D.: A better way to compress images. Byte 13(1), 215\u2013223 (1988)","journal-title":"Byte"},{"issue":"1","key":"24_CR9","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/83.128028","volume":"1","author":"AE Jacquin","year":"1992","unstructured":"Jacquin, A.E.: Image coding based on a fractal theory of iterated contractive image transformations. IEEE Trans. Image Process. 1(1), 18\u201330 (1992)","journal-title":"IEEE Trans. Image Process."},{"issue":"4","key":"24_CR10","first-page":"603","volume":"28","author":"Y Xu","year":"2006","unstructured":"Xu, Y., Wang, J.-J.: Fractal coding based image retrieval using histogram of collage errors. J. Electron. Inf. Technol. 28(4), 603\u2013605 (2006)","journal-title":"J. Electron. Inf. Technol."}],"container-title":["Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","Machine Learning and Intelligent Communications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-04409-0_24","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,13]],"date-time":"2023-02-13T23:47:56Z","timestamp":1676332076000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-04409-0_24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031044083","9783031044090"],"references-count":10,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-04409-0_24","relation":{},"ISSN":["1867-8211","1867-822X"],"issn-type":[{"type":"print","value":"1867-8211"},{"type":"electronic","value":"1867-822X"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"18 May 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MLICOM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Machine Learning and Intelligent Communications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 November 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 November 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mlicom2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EAI Confy +","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"58","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"28","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"48% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}