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37 articles for “segmented image”
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Research ArticleOpen accessPhrase in the titleStatic Hand Gestures: Fingertips Detection Based on Segmented ImagesAhmad Yahya Dawod, Md Jan Nordin, Junaidi AbdullahFingertips detection is important for recognition of static gesture in sign language. This paper presents a new method that is based on YCbCr colour space and skeletonization for fingertips detection towards gesture segmentation and recognition. The method begins with the conversion of an image in RGB colour space into YCbCr colour space. Then, the chrominance Cb and Cr are extracted … …Journal of Computer Science, Vol. 11, Issue 12 · 4 Feb 2016 · 7,032 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDot Detection of Braille Images Using A Mixture of Beta DistributionsAmany Al-Saleh, Ali El-Zaart, Abdul Malik Al-SalmanProblem statement: Braille is a tactile format of written communication for people with low vision and blindness worldwide. Optical Braille Recognition (OBR) offers many benefits to Braille users and people who work with them. Approach: This study presents an algorithm for detecting dots composing braille characters in an image of embossed braille material obtained by an optical scanner. We assumed … …Journal of Computer Science, Vol. 7, Issue 11 · 6 Sep 2011 · 7,436 accessesView PDFCite
Research ArticleOpen accessIn the abstractLeveraging Modified Cascaded Fully Convolutional Neural Networks and Optimized Swin U-Net for Liver Lesion PredictionSugandha Chakraverti, Tejaswi Khanna, Vijay ShuklaLiver lesions are abnormal growths that can develop for various reasons, some of which are noncancerous (benign) while others are cancerous. Machine learning and, deep learning techniques are employed for liver health assessment and lesion detection, but the quality and, diversity of training data can hinder the performance, leading to overfitting or underfitting. These models often need extensive pre-processing and … …Journal of Computer Science, Vol. 22, Issue 10 · 8 Oct 2026 · 372 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Plant Disease Identification Through Hyperspectral Imaging and AC-FNet FrameworkDhason Lita Pansy, Malaichamy MuraliThe precise identification of plant diseases is essential for optimizing agricultural practices. The impact of these diseases on food production often leads to significant revenue loss. Detecting diseases that primarily manifest symptoms in plant leaves has conventionally depended on visual inspection by plant pathologists. However, modern methodologies use machine learning and computer vision techniques to facilitate disease identification, thus addressing … …Journal of Computer Science, Vol. 21, Issue 5 · 21 May 2025 · 8,568 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Impact of XRF-Escape on Energy Resolution of NaI: Tl Scintillation Detectors for Medical Imaging or Gamma-Ray SpectroscopyRaffaele Scafè, Marco Puccini, Rosanna Pellegrini, Roberto PaniThe effect of escape of X-ray fluorescence from scintillator elemental components on the detector energy resolution is investigated from a spectroscopic standpoint, for monolithic and pixelated crystals. Along with these, any other emissions in a given region of interest were also considered. In present spectral evaluations a range of ratios between the areas of the peaks (XRFesc) to (XRFesc + … …American Journal of Applied Sciences, Vol. 21, Issue 1 · 10 Jul 2024 · 5,024 accessesView PDFCite
Research ArticleOpen accessIn the abstractNon-Hodgkin Lymphoma Risk Grading Through the Pathological Data by Using the Optimized Convolutional Lymphnet ModelSivaranjini Nagarajan, Gomathi MuthuswamyDiagnosing Non-Hodgkin Lymphoma (NHL) is difficult and often requires specialised training and expertise as well as extensive morphological investigation and, in certain cases, costly immunohistological and genetic techniques. Computational approaches enabling morphological-based decision making are necessary for bridging the existing gaps. Histopathological images can be accurately classified using deep learning approaches, however data on NHL subtyping is limited. However, there … …Journal of Computer Science, Vol. 20, Issue 5 · 28 Feb 2024 · 4,545 accessesView PDFCite
Research ArticleOpen accessIn the abstractCrop Disease Detection Using Deep Learning Techniques on ImagesKinjal Vijaybhai Deputy, Kalpdrum Passi, Chakresh Kumar JainAgriculture plays a crucial role in the economic development of many countries and sustains the global population despite facing various challenges like climate change, pollinator decline, and plant diseases. These threats to food security highlight the need for innovative solutions to prevent crop loss. Leveraging smartphone technology for automated image recognition-based disease diagnosis has emerged as a promising approach, thanks … …Journal of Computer Science, Vol. 19, Issue 12 · 25 Oct 2023 · 7,497 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Approach to Recognise Odia Characters by Extracting Features from Fragmented QuadrantsAradhana Kar, Sateesh Kumar PradhanThe system introduced in this study concentrates on the recognition of Odia characters. The input to the system is an image in .jpg format which has been created by scanning a document or converting a document to an image by software. The document consists of all Odia alphabets written using the font family 'AkrutiOriAshok-99' in a particular font size in … …Journal of Computer Science, Vol. 19, Issue 1 · 17 Jan 2023 · 6,393 accessesView PDFCite
Research ArticleOpen accessIn the abstractAutomatic Diagnosis of Soybean Leaf Disease by Transfer LearningXiao Yu, Qi Gong, Cong Chen, Lina LuSoybean diseases and insect pests are important factors that affect the output and quality of soybeans, thus it is necessary to do correct inspection and diagnosis of them. For this reason, based on improved transfer learning, this study proposed a classification method for soybean leaf diseases. Firstly, leaves were segmented from the whole image after removing the complicated background images. … …American Journal of Biochemistry and Biotechnology, Vol. 18, Issue 2 · 29 Jun 2022 · 5,807 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