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77 results for “Edge Detection”
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Research ArticleOpen accessIn the keywordsFPGA IMPLEMENTATION AND ANALYSIS OF IMPULSE NOISE REDUCTION IN IMAGESP. Thirumurugan, S. Sasikumar, C. SugapriyaThe images are affected by random valued impulse noises during the image capturing and processing stages. In this study, an efficient, high performance and low hardware utilized impulse noise reduction algorithm is presented. This methodology determines the optimum direction pixels through the estimation of standard deviation. The edges in the images are preserved during the process of impulse noise detection … …American Journal of Applied Sciences, Vol. 11, Issue 7 · 19 Apr 2014 · 7,200 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAutomatic Mouth Localization Using Edge ProjectionMohamed RizonProblem statement: This study presented algorithms to detect mouth from color and intensity images. Approach: First, this algorithm detected the face region in the image and extracts intensity valleys from the face region. Next, the algorithm extracted iris candidates from the valleys and computed the costs for each pair of iris candidates. Finally, a pair of iris candidates was selected … …Journal of Computer Science, Vol. 6, Issue 7 · 31 Jul 2010 · 6,877 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Practical Approach of Selecting the Edge Detector Parameters to Achieve a Good Edge Map of the Gray ImageAkram A. Moustafa, Ziad A. AlqadiProblem statement: practical approach of detecting edge map was proposed. Approach: The methodology of this approach was presented and tested in order to select the best value of the operator, used to smooth and get the gradient, and the threshold value used to convert the gray gradient to binary edge map, so a practical value of the threshold and edge … …Journal of Computer Science, Vol. 5, Issue 5 · 30 May 2009 · 6,794 accessesView PDFCite
Research ArticleOpen accessIn the keywordsObject Detection using Circular Hough TransformMohamed Rizon, Haniza Yazid, Puteh Saad et al.In this study we propose a new system to detect the object from an input image. The proposed system first uses the separability filter proposed by Fukui and Yamaguchi (Trans. IEICE Japan J80-D-II. 8, 2170-2177, 1997) to obtain the best object candidates and next, the system uses the Circular Hough Transform (CHT) to detect the presence of circular shape. The … …American Journal of Applied Sciences, Vol. 2, Issue 12 · 31 Dec 2005 · 8,216 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Survey of Content-Based Video RetrievalP. Geetha, Vasumathi NarayananThis study surveys current trends/methods in video retrieval. The major themes covered by the study include shot segmentation, key frame extraction, feature extraction, clustering, indexing and video retrieval-by similarity, probabilistic, transformational, refinement and relevance feedback. This work has done in an aim to assist the upcoming researchers in the field of video retrieval, to know about the techniques and methods … …Journal of Computer Science, Vol. 4, Issue 6 · 30 Jun 2008 · 8,579 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Scalable Hybrid CNN-LSTM and SDN Based Architecture for Real-Time DDoS Defence in IoT and Cloud NetworksSujit Sutradhar, Joy Lal Sarkar, Rajesh Kumar VermaDistributed Denial-of-Service (DDoS) is one of the most significant threats to the security of IoT, cloud, and Software-Defined Network (SDN) environments because it can aggravate network unavailability and disrupt the continuity of services. This study presents a hybrid CNN-LSTM-based DDoS detection and mitigation system for real-time DDoS detection in the context of heterogeneous network environments, which is integrated with SDN … …Journal of Computer Science, Vol. 22, Issue 10 · 19 Oct 2026 · 508 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdvancing Digital Forgery Detection: A Comparative Analysis of U-Net, Buster Net, Efficient B0+ U-Net, and VGG 16+ U-Net ModelsPreeti Dhiman, Usha ChauhanForgery Detection in the area of digital images is indispensable for insuring authenticity, particularly in detecting Copy-Move, Splicing. In this research, a meticulous analysis of latest learning architectures i.e. U-Net, Buster Net, Efficient B0+U-Net and VGG16+U-Net are compared for the detecting these types of forgeries. U-Net is popular due to its potent segmentation capabilities to provide pixel-level forgery localization while … …Journal of Computer Science, Vol. 22, Issue 10 · 8 Oct 2026 · 383 accessesView PDFCite
Research ArticleOpen accessIn the abstractDual-Branch Shape Texture Learning With Pyramid Residual and Sobel Edge Layers for Rice Variety ClassificationM Pradeep, M SiddappaAutomated rice variety classification categorizes rice types based on features, such as grain texture, shape, color, and size. Traditional handcrafted feature-based models fail at rice classification due to lighting variations, background noise, and environmental conditions, leading to overlapping visual characteristics and frequent misclassification. To address these challenges, this research proposes a novel Dual-Branch Convolutional Neural Network with Pyramid Residual Units … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 627 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Systematic Review of Artificial Intelligence and Deep Learning Approaches for Cocoa Pod Disease DetectionHenry Techie-Menson, Michael Asante, Yaw Marfo Missah et al.Cocoa pod diseases destroy an estimated 700,000 metric tons of cocoa annually, threatening 40–50 million smallholder farmers across tropical regions. Accurate field diagnosis remains constrained by symptom similarity, labour-intensive scouting, and limited specialist access in remote communities. This paper presents a PRISMA-guided systematic review of 25 peer-reviewed studies on automated cocoa pod disease detection and classification (2016–2026), addressing architectural approaches, … …Journal of Computer Science, Vol. 22, Issue 8 · 8 Sep 2026 · 733 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Sentiment Analysis Approach for Affective State Recognition With SWISH-Activated DenseNet-169 in Human Event ForecastingKarthik Elangovan, Prabhakaran Paulraj, Dinesh Babu G L et al.Detecting human feelings from images is perhaps one of the most useful and challenging social communication problems in research. Emotion detection-based deep computing outperforms classic image processing techniques. Facial recognition technology has permeated every aspect of our daily lives, from unlocking our phones to getting private file access on our systems. Machine Learning and Deep Learning make it easy to … …Journal of Computer Science, Vol. 22, Issue 8 · 29 Jul 2026 · 1,211 accessesView PDFCite