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65 results for “range image”
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Research ArticleOpen accessPhrase in the titleA New Approach for 3D Range Image Segmentation using Gradient MethodDina A. Hafiz, Walaa M. Sheta, Sahar Bayoumi, Bayumy A.B. YoussefProblem statement: Segmentation of 3D range images is widely used in computer vision as an essential pre-processing step before the methods of high-level vision can be applied. Segmentation aims to study and recognize the features of range image such as 3D edges, connected surfaces and smooth regions. Approach: This study presents new improvements in segmentation of terrestrial 3D range images … …Journal of Computer Science, Vol. 7, Issue 4 · 4 Apr 2011 · 19,592 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleRange Image Segmentation by Randomized Region Growing and Bayesian Edge RegularizationSmaine Mazouzi, Mohamed BatoucheWe presented and evaluated a new Bayesian method for range image segmentation. The method proceeds in to stages. First, an initial segmentation was produced by a randomized region growing technique. The produced segmentation was considered as a degraded version of the ideal segmentation, which should be then refined. In the second stage, image pixels not labeled in the first stage … …Journal of Computer Science, Vol. 3, Issue 5 · 31 May 2007 · 6,924 accessesView PDFCite
Review ArticleOpen accessIn the abstractUnleashing the Power of Image Denoising: A Comprehensive Review of Classical to Deep Learning MethodsArchana Saini, Ayush DograImage denoising is a vital step in many image processing and computer vision professions that aims to improve picture quality by decreasing noise while maintaining important image information. In this article, a detailed overview is presented of traditional and deep learning based picture denoising approaches. Classical methods, such as linear filtering, transform domain techniques, and patch-based approaches like Non-Local Means … …Journal of Computer Science, Vol. 21, Issue 8 · 8 Oct 2025 · 3,107 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Feature Extraction Dual DCT-DWT Image Watermarking Combined with Chaos-Based CryptosystemKumari Rinki, Pushpneel Verma, Tanupriya Choudhury, Bhupesh Kumar SinghAs a result of the emerging technologies such as Internet-of-Things (IoT), data analysis and automation in many aspects of identity, watermarking has become increasingly important. A majority of prior systems focused on watermark embedding and recovery techniques for binary and grey-scale images in one specified region of the cover image, making the system less dependable. This study develops a novel … …Journal of Computer Science, Vol. 17, Issue 10 · 13 Nov 2021 · 6,094 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Optimized YOLOv11-Based Deep Learning Framework With CNN Feature Enhancement for Tile Crack DetectionVinod Kumar Pal, Pankaj MudholkarThe tile business is a critical part of the national economic development, as it is one of the areas that provides employment, produces goods, and exports them. Regardless of its significance, there are challenges in the industry that are caused by issues with production, which in most cases is caused by low-quality materials used or by mishandling of the products … …Journal of Computer Science, Vol. 22, Issue 8 · 12 Aug 2026 · 979 accessesView PDFCite
Research ArticleOpen accessIn the abstractImplementation and Performance Evaluation of YOLOv8 for Wheat Fungal Disease DetectionShivani Sood, Shallu Duggal, Monika Sethi et al.Among the many difficulties in producing wheat, a vital food source for the world, there are biotic variables like fungal diseases, which drastically lower crop output. Around the world, biotrophic fungi particularly, leaf rust, powdery mildew, and yellow rusts-have become a constant threat to wheat production. Traditional methods of identification and mitigation are labor-intensive, slow, and imprecise, limiting therefore early … …Journal of Computer Science, Vol. 22, Issue 4 · 2 May 2026 · 1,599 accessesView PDFCite
Research ArticleOpen accessIn the abstractMultilevel 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 accessIn the abstractLocal 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 accessIn the abstractImage Thresholding Using the Complement FeatureSalah AmeerA new feature (the complement feature) is proposed in an Eigen formulations for performing global image thresholding. The goal is to find an intensity or gray-level value below which is the background while above it is the foreground (object). Each pixel in the image is represented by a (2D) unit vector where the x-component is the normalized (to [0,1] or … …American Journal of Engineering and Applied Sciences, Vol. 13, Issue 2 · 8 Jun 2020 · 6,505 accessesView PDFCite