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@article{192760,
        author = {Komal and Bindia Handa and Dr. Isha Malhotra},
        title = {Face Recognition using textural features and KNN},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {9},
        pages = {2828-2833},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=192760},
        abstract = {Texture features are the very important parameter in the field of image classification and identification. Texture feature-based descriptor are very efficient in face detection and recognition, expression recognition, and in recognizing different component of the face. In this work, face recognition using textural features and k-nearest neighbor has been proposed. In this research, recognition process involves two phases. In first phase some pre-existing techniques are used to detect the face and then gray level co-occurrence matrix (GLCM) is considered from the detected face image after that some statistical texture structures are obtained. In the second segment, these textural features are classified using k-NN classifier. And accuracy of the proposed technique is calculated.},
        keywords = {texture features; classifier; texture classification; feature extraction; k-nearest neighbour.},
        month = {February},
        }