Research ArticleOpen accessAll words, across the recordMultilevel Image Thresholding Using the Complement FeatureSalah AmeerA novel Eigen formulation is proposed for image segmentation. Each pixel is represented by a unit vector having the x-component as the normalized gray value of the pixel. The axes of inertia are simply the Eigen vectors of the auto-correlation matrix. The largest Eigen vector is used as the point of split. Each sub-image is further split in the same … …American Journal of Engineering and Applied Sciences, Vol. 13, Issue 3 · 28 Aug 2020 · 5,917 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordLocal Features Supported by the Complement Feature for Image SegmentationSalah AmeerAn Eigen formulation is proposed for image thresholding/segmentation. A vector composed of local features, normalized intensity of each pixel and that of the neighboring pixels, is used to represent each pixel. A “complement” component is appended to this vector to produce a “unit” vector. The auto-correlation matrix is computed for each pixel in the image using this unit vector. The … …American Journal of Engineering and Applied Sciences, Vol. 13, Issue 3 · 7 Jul 2020 · 6,602 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordBoosting Kernel Discriminative Common Vectors for Face RecognitionC. Lakshmi, M. PonnavaikkoProblem statement: Kernel discriminative common vector (KDCV) was one of the most effective non-linear techniques for feature extraction from high dimensional data including images and text data. Approach: This study presented a new algorithm called Boosting Kernel Discriminative Common Vector (BKDCV) to further improve the overall performance of KDCV by integrating the boosting and KDCV techniques. Results: In BKDCV, the … …Journal of Computer Science, Vol. 5, Issue 11 · 30 Nov 2009 · 6,571 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordFace Recognition using Eigenfaces and Neural NetworksMohamed Rizon, Muhammad Firdaus Hashim, Puteh Saad et al.In this study, we develop a computational model to identify the face of an unknown person’s by applying eigenfaces. The eigenfaces has been applied to extract the basic face of the human face images. The eigenfaces is then projecting onto human faces to identify unique features vectors. This significant features vector can be used to identify an unknown face by … …American Journal of Applied Sciences, Vol. 3, Issue 6 · 30 Jun 2006 · 6,940 accessesView PDFCite