{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:45:40Z","timestamp":1760143540982,"version":"build-2065373602"},"reference-count":29,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2024,2,13]],"date-time":"2024-02-13T00:00:00Z","timestamp":1707782400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>This paper proposes the transformation\u00a0S\u2192C\u2192, where S is a digital gray-level image and\u00a0C\u2192\u00a0is a vector expressed through the textural space. The proposed transformation is denominated Vectorial Image Representation on the Texture Space (VIR-TS), given that the digital image S is represented by the textural vector\u00a0C\u2192. This vector\u00a0C\u2192\u00a0contains all of the local texture characteristics in the image of interest, and the texture unit\u00a0T\u2192\u00a0entertains a vectorial character, since it is defined through the resolution of a homogeneous equation system. For the application of this transformation, a new classifier for multiple classes is proposed in the texture space, where the vector\u00a0C\u2192\u00a0is employed as a characteristics vector. To verify its efficiency, it was experimentally deployed for the recognition of digital images of tree barks, obtaining an effective performance. In these experiments, the parametric value \u03bb employed to solve the homogeneous equation system does not affect the results of the image classification. The VIR-TS transform possesses potential applications in specific tasks, such as locating missing persons, and the analysis and classification of diagnostic and medical images.<\/jats:p>","DOI":"10.3390\/jimaging10020048","type":"journal-article","created":{"date-parts":[[2024,2,14]],"date-time":"2024-02-14T06:59:26Z","timestamp":1707893966000},"page":"48","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Vectorial Image Representation for Image Classification"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4018-672X","authenticated-orcid":false,"given":"Maria-Eugenia","family":"S\u00e1nchez-Morales","sequence":"first","affiliation":[{"name":"Departamento de Ciencias Tecnol\u00f3gicas, Centro Universitario de la Ci\u00e9nega, Universidad de Guadalajara, Av. Universidad No. 1115, Lindavista, Ocotl\u00e1n 47810, Jalisco, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0041-3932","authenticated-orcid":false,"given":"Jos\u00e9-Trinidad","family":"Guillen-Bonilla","sequence":"additional","affiliation":[{"name":"Departamento de Electro-Fot\u00f3nica, Centro Universitario de Ciencias Exactas e Ingenier\u00edas, Universidad de Guadalajara, Blvd. M. Garc\u00eda Barrag\u00e1n 1421, Guadalajara 44410, Jalisco, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8029-017X","authenticated-orcid":false,"given":"H\u00e9ctor","family":"Guillen-Bonilla","sequence":"additional","affiliation":[{"name":"Departamento de Ingenier\u00eda de Proyectos, Centro Universitario de Ciencias Exactas e Ingenier\u00edas, Universidad de Guadalajara, Blvd-M. Garc\u00eda Barrag\u00e1n 1421, Guadalajara 44410, Jalisco, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alex","family":"Guillen-Bonilla","sequence":"additional","affiliation":[{"name":"Departamento de Ciencias Computacionales e Ingenier\u00edas, Centro Universitario de los Valles, Universidad de Guadalajara, Carretera Guadalajara-Ameca Km. 45.5, Ameca 46600, Jalisco, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3283-5569","authenticated-orcid":false,"given":"Jorge","family":"Aguilar-Santiago","sequence":"additional","affiliation":[{"name":"Departamento de Ciencias B\u00e1sicas, Centro Universitario de la Ci\u00e9nega, Universidad de Guadalajara, Av. 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[Ph.D. Thesis, University of Southern California].","DOI":"10.21236\/ADA083283"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.patrec.2023.04.006","article-title":"Large-margin representation learning for texture classification","volume":"170","author":"Britto","year":"2023","journal-title":"Pattern Recognit. Lett."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Aguilar Santiago, J., Guillen Bonilla, J.T., Garcia Ram\u00edrez, M.A., and Jim\u00e9nez Rodr\u00edguez, M. (2023). Identification of Lacerations Caused by Cervical Cancer through a comparative study among texture-extraction techniques. Appl. Sci., 13.","DOI":"10.3390\/app13148292"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Sharma, R., Kumar Mahanti, G., Panda, G., Rath, A., Dash, S., Mallik, S., and Hu, R. (2023). A framework for detecting thyroid cancer from ultrasound and histopathological images using deep learning, meta-heuristics and MCDM algorithms. J. Image, 9.","DOI":"10.3390\/jimaging9090173"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.patrec.2020.09.035","article-title":"Adaptive columetric texture segmentation based on Gaussian Markov random fields features","volume":"140","author":"Almakady","year":"2020","journal-title":"Pattern Recognit. Lett."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"103909","DOI":"10.1016\/j.jvcir.2023.103909","article-title":"A dual-task regi\u00f3n-boundary aware neural network for accurate pulmonary nodule segmentation","volume":"96","author":"Qiu","year":"2023","journal-title":"J. Vis. Commun. Image Represent."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Anderson, K., Richardson, J., Lennartson, B., and Fabian, M. (2006, January 8\u201310). Sinthesis of hierarchical and distributed control functions for multi-product manufacturing cells. Proceedings of the 2006 IEEE International Conference on Automation Sciences and Engineering, Shanghai, China.","DOI":"10.1109\/COASE.2006.326902"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1109\/MCG.2005.79","article-title":"Geometric texture modeling","volume":"25","author":"Elber","year":"2005","journal-title":"IEEE Comput. Graph. Appl."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/S0167-8655(02)00185-X","article-title":"A framework for texture classification using the coordinated clusters representation","volume":"24","author":"Kurmyshev","year":"2003","journal-title":"Pattern Recognit. Lett."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1007\/s11554-022-01208-0","article-title":"GUD-Canny: A real-time GPU-based unsupervised and distributed Canny edge detector","volume":"19","year":"2022","journal-title":"J. Real-Time Image Process."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1007\/s11554-023-01353-0","article-title":"An integrated and real-time social distancing, mask detection, and facial temperature video measurement system for pandemic monitoring","volume":"20","author":"Elhanashi","year":"2023","journal-title":"J. Real-Time Image Process."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1765","DOI":"10.1007\/s11554-020-00944-5","article-title":"An FPGA-based desing for real-time super-resolution reconstruction","volume":"17","author":"Marin","year":"2020","journal-title":"J. Real-Time Image Process."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1007\/s11263-009-0220-6","article-title":"Viewpoint invariant texture description using fractal analysis","volume":"83","author":"Xu","year":"2009","journal-title":"Int. J. Comput. Vis."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"109011","DOI":"10.1016\/j.sigpro.2023.109011","article-title":"Mixture of multivariate generalized Gaussians fr multi-band texture modeling and representation","volume":"209","author":"Yapi","year":"2023","journal-title":"Signal Process."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"109097","DOI":"10.1016\/j.sigpro.2023.109097","article-title":"Probabilistic quaternion collaborative representation and its application to robust color face identification","volume":"210","author":"Zou","year":"2023","journal-title":"Signal Process."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"108843","DOI":"10.1016\/j.patcog.2022.108843","article-title":"Using global information to refine local patterns for texture representation and classification","volume":"131","author":"Shu","year":"2022","journal-title":"Pattern Recognit."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"109959","DOI":"10.1016\/j.patcog.2023.109959","article-title":"Enhancing texture representation with deep tracing pattern encoding","volume":"146","author":"Chen","year":"2024","journal-title":"Pattern Recognit."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"109802","DOI":"10.1016\/j.patcog.2023.109802","article-title":"RADAM: Texture recognition through randomized aggregated encoding of dee activation maps","volume":"143","author":"Scabini","year":"2023","journal-title":"Pattern Recognit."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1503","DOI":"10.1016\/S0167-8655(02)00389-6","article-title":"One-class texture classifier in the CCR feature space","volume":"24","author":"Kurmyshev","year":"2003","journal-title":"Pattern Recognit. Lett."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"109731","DOI":"10.1016\/j.patcog.2023.109731","article-title":"Resampling approach for one-class classification","volume":"143","author":"Lee","year":"2023","journal-title":"Pattern Recognit."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1007\/s10851-012-0349-8","article-title":"Texture description through histograms of equivalent patterns","volume":"45","author":"Bianconi","year":"2013","journal-title":"J. Math. Imaging Vis."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"643","DOI":"10.1016\/j.future.2019.09.015","article-title":"Cervical cancer classification using convolutional neural networks and extreme learning machines","volume":"102","author":"Ghoneim","year":"2020","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1162","DOI":"10.1049\/cmu2.12601","article-title":"A novel technique for texture description and image classification based in RGB compositions","volume":"17","year":"2023","journal-title":"IET Commun."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1346","DOI":"10.1016\/j.patrec.2004.11.028","article-title":"Comparative experiment with colour texture classifiers using the CCR feature space","volume":"26","author":"Kurmyshev","year":"2005","journal-title":"Pattern Recognit. Lett."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"5562","DOI":"10.1364\/AO.46.005562","article-title":"Quantifying a similarity of classes of texture image","volume":"46","author":"Kurmyshev","year":"2007","journal-title":"Appl. Opt."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Gonz\u00e1lez-Castro, V., Cernadas, E., Huelga, E., Fern\u00e1ndez-Delgado, M., Porto, J., Antunez, J.R., and Souto-Bayarri, M. (2020). CT Radiomics in Colorectal Cancer: Detection of KRAS Mutation Using Texture Analysis and Machine Learning. Appl. Sci., 10.","DOI":"10.3390\/app10186214"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"16143","DOI":"10.1038\/s41598-021-95748-3","article-title":"Comparison of machine and deep learning for the classification of cervical cancer based on cervicography images","volume":"11","author":"Park","year":"2021","journal-title":"Sci. Rep."},{"key":"ref_28","first-page":"54","article-title":"Is the Coordinated Clusters Representation an analog of the Local Binary Pattern?","volume":"14","author":"Kurmyshev","year":"2010","journal-title":"Comput. Sist."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"718","DOI":"10.1016\/j.optlaseng.2010.12.014","article-title":"Complexity reduced coding of binary pattern units in image classification","volume":"49","author":"Kurmyshev","year":"2011","journal-title":"Opt. 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