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"journal" : { "otype" : "Journal", "mtid" : 10031308, "link" : "/api/journal/10031308", "label" : "IEEE ACCESS 2169-3536 2169-3536", "pIssn" : "2169-3536", "eIssn" : "2169-3536", "reviewType" : "REVIEWED", "noIF" : false, "sciIndexed" : true, "scopusIndexed" : true, "lang" : "FOREIGN", "hungarian" : false, "published" : true, "oldId" : 10031308, "snippet" : true }, "volume" : "10", "firstPage" : "75074", "lastPage" : "75096", "firstPageOrInternalIdForSort" : "75074", "pageLength" : 23, "publishedYear" : 2022, "abstractText" : "Color harmony is the hotspot of many researchers in the fields of art and design which is widely used in various artworks and design activities. As for psychology, color harmony is closely related to human's perception and cognition, although, the research of its generation process has not been fully focused on. With experimental psychology with artificial intelligence technology combined together, our aim is to investigate the factors affecting color harmony on the basis of the generation process from perception to cognition, and construct a mathematical model to predict its degree, so as to realize the quantitatively analysis and measurement of color harmony. We classify the factors affecting color harmony into objective and subjective ones. Among them, the objective factors are constructed based on the three principle elements of color with a total of 21-dimensional color-pair objective physical features extracted. And the subjective factors are divided into direct psychological effects and indirect psychological effects. 180 two-color combinations were evaluated by 30 subjects based on color harmony and its subjective factors on discrete scales ranging from -2 to 2. Correlation analysis reveals that color harmony is not only affected by objective factors, but also by subjective factors which has a stronger correlation than that of the objective ones. Finally, machine learning algorithms were adopted to construct a mathematical model, which has been proved that the linear relationship can well explain the generation mechanism of color harmony.", "subjects" : [ { "otype" : "Classification", "mtid" : 10034, "link" : "/api/classification/10034", "label" : "Számítás- és információtudomány", "published" : true, "snippet" : true }, { "otype" : "Classification", "mtid" : 10880, "link" : "/api/classification/10880", "label" : "Villamosmérnöki és informatikai tudományok", "published" : true, "snippet" : true } ], "keywords" : [ { "otype" : "Keyword", "mtid" : 1650, "link" : "/api/keyword/1650", "label" : "COLOR", "published" : true, "oldId" : 1650, "snippet" : true }, { "otype" : "Keyword", "mtid" : 3673, "link" : "/api/keyword/3673", "label" : "Mathematical models", "published" : true, "oldId" : 3673, "snippet" : true }, { "otype" : "Keyword", "mtid" : 3695, "link" : "/api/keyword/3695", "label" : "Feature extraction", "published" : true, "oldId" : 3695, "snippet" : true }, { "otype" : "Keyword", "mtid" : 5930, "link" : "/api/keyword/5930", "label" : "Psychology", "published" : true, "oldId" : 5930, "snippet" : true }, { "otype" : "Keyword", "mtid" : 5962, "link" : "/api/keyword/5962", "label" : "cognition", "published" : true, "oldId" : 5962, "snippet" : true }, { "otype" : "Keyword", "mtid" : 12390, "link" : "/api/keyword/12390", "label" : "machine learning", "published" : true, "oldId" : 12390, "snippet" : true }, { "otype" : "Keyword", "mtid" : 1026086, "link" : "/api/keyword/1026086", "label" : "BRIGHTNESS", "published" : true, "oldId" : 1026086, "snippet" : true }, { "otype" : "Keyword", "mtid" : 1103360, "link" : "/api/keyword/1103360", "label" : "color harmony", "published" : true, "oldId" : 1103360, "snippet" : true }, { "otype" : "Keyword", "mtid" : 1305594, "link" : "/api/keyword/1305594", "label" : "Image color analysis", "published" : true, "oldId" : 1305594, "snippet" : true }, { "otype" : "Keyword", "mtid" : 1666956, "link" : "/api/keyword/1666956", "label" : "color emotion", "published" : true, "snippet" : true }, { "otype" : "Keyword", "mtid" : 2125212, "link" : "/api/keyword/2125212", "label" : "experimental psychology", "published" : true, "snippet" : true }, { "otype" : "Keyword", "mtid" : 2763628, "link" : "/api/keyword/2763628", "label" : "objective factor", "published" : true, "snippet" : true }, { "otype" : "Keyword", "mtid" : 2763629, "link" : "/api/keyword/2763629", "label" : "subjective factor", "published" : true, "snippet" : true }, { "otype" : "Keyword", "mtid" : 2763630, "link" : "/api/keyword/2763630", "label" : "hierarchy model of color harmony generation", "published" : true, "snippet" : true } ], "digital" : null, "printed" : null, "sourceYear" : 2022, "foreignEdition" : true, "foreignLanguage" : true, "fullPublication" : true, "conferencePublication" : false, "nationalOrigin" : null, "missingAuthor" : false, "oaType" : "GOLD", "oaCheckDate" : "2022-10-21", "oaFree" : false, "citationCount" : 0, "citationCountUnpublished" : 0, "citationCountWoOther" : 0, "independentCitCountWoOther" : 0, "doiCitationCount" : 0, "wosCitationCount" : 0, "scopusCitationCount" : 0, "independentCitationCount" : 0, "unhandledCitationCount" : 0, "citingPubCount" : 0, "independentCitingPubCount" : 0, "unhandledCitingPubCount" : 0, "citedPubCount" : 1, "citedCount" : 1, "ratings" : [ { "otype" : "SjrRating", "mtid" : 11290120, "link" : "/api/sjrrating/11290120", "label" : "sjr:Q1 (2022) Scopus - Computer Science (miscellaneous) IEEE ACCESS 2169-3536", "listPos" : 55, "rankValue" : 0.24, "type" : "journal", "ratingType" : { "otype" : "RatingType", "mtid" : 10002, "link" : "/api/ratingtype/10002", "label" : "sjr", "code" : "sjr", "published" : true, "snippet" : true }, "subject" : { "otype" : "ClassificationExternal", "mtid" : 1701, "link" : "/api/classificationexternal/1701", "label" : "Scopus - Computer Science (miscellaneous)", "published" : true, "oldId" : 1701, "snippet" : true }, "ranking" : "Q1", "calculation" : "FROM_LAST_YEAR", "published" : true, "snippet" : true } ], "ratingsForSort" : "Q1", "hasCitationDuplums" : false, "directInstitutesForSort" : "", "ownerAuthorCount" : 2, "ownerInstituteCount" : 11, "directInstituteCount" : 0, "authorCount" : 6, "contributorCount" : 0, "hasQualityFactor" : true, "link" : "/api/publication/33177925", "label" : "Wang Shuang et al. 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