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Research ArticleOpen accessIn the keywordsSRBIR: Semantic Region Based Image Retrieval by Extracting the Dominant Region and Semantic LearningI. Felci Rajam, S. ValliProblem statement: The Semantic Region Based Image Retrieval (SRBIR) system that automatically segments the dominant foreground region, consisting of the semantic concept of the image, such as elephants, roses and does the semantic learning, is proposed. Approach: The system segments an image into different regions and finds the dominant foreground region in it, which is the semantic concept of that … …Journal of Computer Science, Vol. 7, Issue 3 · 7 Mar 2011 · 7,026 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Effective History-based Background Extraction SystemSeyed Hashem Davarpanah, Fatimah Khalid, Maryam GolchinProblem statement: In many visions-based surveillance systems, the first step is accomplished by detecting moving objects resulted from subtraction of the current captured frame from the extracted background. So, the results of these systems mainly depend on the accuracy of the background image. Approach: In this study, a proposed background extraction system is presented to model the background using a … …Journal of Computer Science, Vol. 8, Issue 7 · 23 May 2012 · 6,998 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Block-Based Multi-Scale Background Extraction AlgorithmSeyed Hashem Davarpanah, Fatimah Khalid, Maryam GolchinProblem statement: To extract the moving objects, vision-based surveillance systems subtract the current image from a predefined background image. The efficiency of these systems mainly depends on accuracy of the extracted background image. It should be able to adapt to the changes continuously. In addition, especially in real-time applications the time complexity of this adaptation is a critical matter. Approach: … …Journal of Computer Science, Vol. 6, Issue 12 · 6 Nov 2010 · 7,213 accessesView PDFCite
Research ArticleOpen accessIn the abstractIncorporation of Modified Region Growing into FCM Clustering for Extraction of Tumors in MR ImagesLovepreet Singh Brar, Jaget Singh, Bhawana Agrawal et al.Due to the tremendous growth of medical Magnetic Resonance (MR) images, it becomes an essential requirement for an automated extraction of diagnostically salient parts of the images to refine the transmission and storage process. Research method: This paper proposes an automated unsupervised machine learning segmentation technique named fuzzy c-means clustering based on modified region growing algorithm (RG-FCM) for the extraction … …Journal of Computer Science, Vol. 21, Issue 12 · 12 Feb 2026 · 1,477 accessesView PDFCite
Research ArticleOpen accessIn the abstractUnsupervised Cosegmentation Model based on Saliency Detection and Optimized Hue Saturation Value Features of SuperpixelsRasha Shoitan, Mona M. MoussaSegmenting out the foreground from a single image remains a challenge in computer vision. Image co-segmentation has been used recently to alleviate the single image segmentation by exploiting the information of the common object to be segmented from a group of images having the same object. This research proposes an unsupervised co-segmentation technique based on saliency detection and optimized features … …Journal of Computer Science, Vol. 17, Issue 7 · 3 Aug 2021 · 7,003 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
Research ArticleOpen accessIn the abstractHistogram Matching Schemes for Image ThresholdingSalah AmeerThis paper proposes several novel schemes for image thresholding. The idea is simply to compare the original image histogram to that of the thresholded image. Element by element comparison (sum of absolute difference between the two histograms) is found to be of better performance than a single feature (area or size) comparison. The optimum threshold is the one producing the … …American Journal of Engineering and Applied Sciences, Vol. 12, Issue 3 · 9 Sep 2019 · 7,872 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Improved Object Detection Technique for Hazard Avoidance SystemsSupreet Kaur Deol, P.W.C. Prasad, Abeer Alsadoon, A. ElchouemiHazard detection and avoidance at construction sites working with heavy equipment and moving vehicles is one of the biggest issues in modern surveillance. Background subtraction using a Gaussian Mixture Model (GMM) is widely utilized for identification of moving objects with most existing methods leading to improvements but lacking accuracy of object detection. This paper aims to improve accuracy and processing … …American Journal of Applied Sciences, Vol. 15, Issue 7 · 27 Sep 2018 · 8,195 accessesView PDFCite
Research ArticleOpen accessIn the abstractImage Binarization Using Block Boundary Pixels MeanO. Imocha Singh, T. Romen SinghInput image pixels classification into two intensities like black and white as foreground and background respectively refers to image binarization. Binarization with a local threshold value is termed as adaptive image binarization. Locally adaptive thresholding techniques are local pixels dependent process. Local environment dependent process is normally time consuming one and hence its computational time complexity is also local region … …Journal of Computer Science, Vol. 13, Issue 11 · 28 Nov 2017 · 7,811 accessesView PDFCite
Research ArticleOpen accessIn the abstractMultiple Vehicle Tracking using Adaptive Gaussian Mixture Model and Kalman FilterFandy Setyo UtomoBased on data from the Central Statistics Agency (BPS) of the Republic of Indonesia in catalog Crime Statistics in 2014, the number of crimes of theft of motor vehicles has increased since 2010 until 2013. Recorded in 2013 the number reached 42.508 cases of theft. In this study, we made a prototype application using Adaptive Gaussian Mixture Models algorithms and … …American Journal of Applied Sciences, Vol. 13, Issue 12 · 22 Dec 2016 · 7,375 accessesView PDFCite