Development of a local binary pattern descriptor for texture analysis using deep convolutional neural network

Development of a local binary pattern descriptor for texture analysis using deep convolutional neural network | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Development of a local binary pattern descriptor for texture analysis using deep convolutional neural network HARDEEP SINGH SINGH, GAGANDEEP GAGAN This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4149753/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract The machine learning is an important branch of artificial intelligence. In machine learning, the facial expression recognition continued a difficult and interesting topic. The majority of extant techniques are based on traditional features descriptors such as local binary patterns and its extended variants. This research paper expresses the strength of deep learning techniques that is the deep convolutional neural networks for classification of faces in selected dataset. We applied proposed Deep CNN architecture with local binary patterns and histogram of oriented gradient method. Viola Jones algorithm is applied for detection of faces from Face Recognition dataset. The features of faces are extracted by Binary Phase Component Analysis and information correlation factor gain. Then the classification of images is performed by our proposed deep convolutional neural network (Deep CNN). The performance of the model is evaluated by accuracy, precision, recall, f1-score and confusion matrix. The architecture of CNN constitutes convolutional layer, max-pooling, dense and flatten layers with dropout. The proposed architecture is validated on the Face Recognition dataset. We obtained 0.98 as accuracy which is the very high accuracy of deep CNN model for classification. LBP CNN HOG Texture Feature extraction Classification Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editor assigned by journal 28 Mar, 2024 Submission checks completed at journal 22 Mar, 2024 First submitted to journal 22 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4149753","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":282747555,"identity":"7bff1e45-e908-4886-aad1-094df0634aca","order_by":0,"name":"HARDEEP SINGH SINGH","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABNklEQVRIie2RMUvDQBSAEwIvy6WuV1LSv5ASiAaH/JVkSZbUxcEORc4lLsU5/gun4hg5vOlCN8lQsFLIIA6VgjjUaq6YLY2Ogvm4B/ce93Hv8SSppeUPYpaBxQXEed2A0ZdoKoq9XynyNelYgwvmiSL6URGWohHDlygXRWmvcqhmT/lqNHc7+uXDQru1PTnm6+d8fIQkld7f1CjOJLSchBd+3ONnZpcHJyrKpscRKxtDQZDXNZYGoGsx9QBHATaBncpJNrUiKBWM7FplVoD+saXuTvHg0yePL4UVbRuUvPxFJlSOccjwXQw+SbmyHMZNSqE4E1bOgiPoEg7WgDBbGV5hBPtmmQVy/j6eu/0kLPTNaLfK5Tp6OzcOVMrqlG/SMpBZZVAttwmhqIsqU1bNr1taWlr+GV8TJmq3SfBn+AAAAABJRU5ErkJggg==","orcid":"","institution":"IKG Punjab Technical University Jalandhar Punjab India","correspondingAuthor":true,"prefix":"","firstName":"HARDEEP","middleName":"SINGH","lastName":"SINGH","suffix":""},{"id":282747556,"identity":"7a4b2ea2-0e29-4ef1-aa88-b6e63502070d","order_by":1,"name":"GAGANDEEP GAGAN","email":"","orcid":"","institution":"IKG Punjab Technical University Jalandhar Punjab India","correspondingAuthor":false,"prefix":"","firstName":"GAGANDEEP","middleName":"","lastName":"GAGAN","suffix":""}],"badges":[],"createdAt":"2024-03-22 12:30:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4149753/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4149753/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53539208,"identity":"e4b63350-479e-41d7-8395-e1086be08c54","added_by":"auto","created_at":"2024-03-27 08:22:06","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":606866,"visible":true,"origin":"","legend":"","description":"","filename":"researchpaperaccordingtojournal.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4149753/v1_covered_32937a54-4986-42d1-807d-4cd071a6ea2a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Development of a local binary pattern descriptor for texture analysis using deep convolutional neural network","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-machine-learning-and-cybernetics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jmlc","sideBox":"Learn more about [International Journal of Machine Learning and Cybernetics](http://actavetscand.biomedcentral.com/)","snPcode":"13042","submissionUrl":"https://submission.nature.com/new-submission/13042/3","title":"International Journal of Machine Learning and Cybernetics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"LBP, CNN, HOG, Texture, Feature extraction, Classification","lastPublishedDoi":"10.21203/rs.3.rs-4149753/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4149753/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe machine learning is an important branch of artificial intelligence. 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