{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,2]],"date-time":"2025-10-02T00:41:42Z","timestamp":1759365702398,"version":"build-2065373602"},"reference-count":64,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Universiti Poly-Tech Malaysia"}],"content-domain":{"domain":["www.mdpi.com"],"crossmark-restriction":true},"short-container-title":["Computers"],"abstract":"<jats:p>Malay songket motifs are a vital component of Malaysia\u2019s intangible cultural heritage, characterized by intricate visual designs and deep cultural symbolism. However, the practical digital preservation and retrieval of these motifs present challenges, particularly due to the rotational variations typical in textile imagery. This study introduces a novel Content-Based Image Retrieval (CBIR) model that integrates Principal Component Analysis (PCA) for feature extraction and Quadratic Geometric Distance (QGD) for measuring similarity. To evaluate the model\u2019s performance, a curated dataset comprising 413 original images and 4956 synthetically rotated songket motif images was utilized. The retrieval system featured metadata-driven preprocessing, dimensionality reduction, and multi-angle similarity assessment to address the issue of rotational invariance comprehensively. Quantitative evaluations using precision, recall, and F-measure metrics demonstrated that the proposed PCAQGD + Rotation technique achieved a mean F-measure of 59.72%, surpassing four benchmark retrieval methods. These findings confirm the model\u2019s capability to accurately retrieve relevant motifs across varying orientations, thus supporting cultural heritage preservation efforts. The integration of PCA and QGD techniques effectively narrows the semantic gap between machine perception and human interpretation of motif designs. Future research should focus on expanding motif datasets and incorporating deep learning approaches to enhance retrieval precision, scalability, and applicability within larger national heritage repositories.<\/jats:p>","DOI":"10.3390\/computers14100416","type":"journal-article","created":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T09:37:21Z","timestamp":1759311441000},"page":"416","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Preserving Songket Heritage Through Intelligent Image Retrieval: A PCA and QGD-Rotational-Based Model"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-0137-6957","authenticated-orcid":false,"given":"Nadiah","family":"Yusof","sequence":"first","affiliation":[{"name":"Faculty of Computing & Multimedia, University Poly-Tech Malaysia, Cheras 56100, Malaysia"}]},{"given":"Nazatul Aini","family":"Abd. Majid","sequence":"additional","affiliation":[{"name":"Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia"}]},{"given":"Amirah","family":"Ismail","sequence":"additional","affiliation":[{"name":"Faculty of Islamic Technology, Sultan Sharif Ali Islamic University, Bandar Seri Begawan BE1310, Brunei"}]},{"given":"Nor Hidayah","family":"Hussain","sequence":"additional","affiliation":[{"name":"Faculty of Creative Multimedia & Computing, Selangor Islamic University, Bangi 43000, Malaysia"}]}],"member":"1968","published-online":{"date-parts":[[2025,10,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"57","DOI":"10.22452\/JOMAS.vol32no2.4","article-title":"Songket Melayu: Serumpun Bangsa Sesantun Budaya","volume":"32","year":"2021","journal-title":"J. Pengaj. 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