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28 articles for “image segmentation”
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Image Segmentation
Abstract: In computer vision, image segmentation is the process of partitioning a digital image into multiple segments (sets of pixels, also known as super-pixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze.[1][2] Image segmentation is typically used to locate objects and boundaries (lines, curves, etc.) in images. More precisely, image segmentation is the process of …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 3, Issue 2, 2017 · pp. 55–56 Read article
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AI-Driven Hybrid Neural Network Architecture for Medical Image Segmentation: A Novel Approach for Early Disease Detection
Abstract: One of the key factors in detecting early diseases is medical image segmentation. Medical image segmentation can be very complex due to the differences in image quality, noise, and specific anatomical structures of individual patients. A novel approach for a hybrid neural network structure that combines the power of convolutional neural networks, and the transformer-based models is described here for improved accuracy and robustness of medical image segmentation. Unlike traditional …
Published in International Journal of Microwave Engineering and Technology · Vol. 11, Issue 1, 2025 · pp. 1–7 Read article
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A Study of Segmentation Techniques for Diagnosing Melanoma in Dermoscopic Images
Abstract: Skin cancer remains among the deadliest forms of cancer, with an average survival rate ranging from 18% to 20%. Detecting and segmenting melanoma early is a challenging yet crucial undertaking. To effectively segment the lesions, several studies have presented automated and standard techniques. Likewise, traditional methods for segmentation frequently require inputs from humans and cannot be applied in automated systems. The aim of this article is to provide a comparative …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 10, Issue 1, 2024 · pp. 1–10 Read article
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Segmentation Refers to the Process of Partitioning a Digital Image into Multiple Regions
Abstract: Abstract Image segmentation is a very important tool in image processing and might function as Associate in Nursing economical face to classy algorithms and thereby alter subsequent process. A typical drawback in segmentation of a monochrome image happens once a picture contains a background of variable grey level like step by step ever-changing shades, regions or categories assume some broad vary of grey scales. This drawback is inherent since intensity …
Published in International Journal of Distributed Computing and Technology · Vol. 1, Issue 1, 2015 · pp. 25–33 Read article
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Using Image Feature Selection through Deep Salient Region Detection Using Canny Edge Detection Framework
Abstract: Salient object identification has received a lot of attention recently in computer vision because it offers quick solutions to several challenging procedures. It first identifies the scene's most prominent and attention-grabbing object, after which it segments the object's entire extent. The perception and processing of visual input is linked to visual saliency. This proposed work focuses on several convectional saliency detection methods that are useful in a variety of applications …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 9, Issue 1, 2023 · pp. 8–21 Read article
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On Image Processing Using MATLAB: A Survey
Abstract: Abstract The digital image processing research has following attributes: Image Acquisition, Image Enhancement, Image Segmentation Feature Extraction and Classification. Each steps of digital image processing research has gone long way in developing the techniques, algorithms and methods. This paper will study the use of MATLAB in the steps of digital image processing research. Record each techniques and algorithms, discuss about the sequential timeline development of the algorithms. The performance of …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 1, Issue 1, 2015 · pp. 28–33 Read article
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Computer-Assisted Automatic Segmentation/Detection of Multiple Sclerosis Lesions in Brain MR Images: A Review
Abstract: In humans, central nervous system (CNS) may suffer with demyelinating disease, named multiple sclerosis (MS), characterized by a wide scope of neurological deficits. Magnetic resonance imaging (MRI) is an important tool for MS diagnosis which enables the detection of location and size of the affected tissue. Research on this disease is has grabbed wide attention so as to improve the treatment plans by better understanding of causes and the disease …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 3, Issue 1, 2017 · pp. 17–24 Read article
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Investigation and Classification of Cardiac MRI Images using Texture Analysis
Abstract: In order to quantify the myocardial viability after infarction, recent researches have developed new cardiac MRI protocol using particle contrast agents which highlight the different areas after infarction: i.e. the healthy area, the necrosed area and the two ischemic areas. Actually the researches are carried out on rodents micro cardiac MRI for which the obtained images are very noisy and present a very low contrast. In this paper, we analyse …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 7, Issue 2, 2021 · pp. 37–41 Read article
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Image Enhancement and Lung Cancer Detection Using Anisotropic Diffusion Filter
Abstract: The leading cause of cancer-related deaths globally is lung cancer. According to the Global Cancer Statistics lung cancer is the leading cause of cancer-related fatalities with 1.8 million deaths and 2.1 million new cases. Early detection of a tiny tumor can stop cancer from spreading and greatly enhance prognosis and survival rates. Consequently, the creation of a sophisticated computer-aided diagnosis system (CADS) may be advantageous for the early therapy of …
Published in International Journal of Analytical and Applied Chemistry · Vol. 9, Issue 1, 2023 · pp. 21–29 Read article
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Blood Cell Subtype Classification Using Deep Learning
Abstract: A vital component of human bodies is blood. Despite making up only 1% of the human body, blood cells have a greater impact on disease and infection detection. These blood cell subtype classifications also aid in ensuring that patients receive the quickest-acting medical treatment and recover swiftly. To get the findings, many machine learning techniques are used, including the Feature Extraction methods (K* classifier and Decision table) and the Image …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 9, Issue 1, 2023 · pp. 37–45 Read article
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Enhancement K-Mean Algorithm (EKM) for Image Processing in MATLAB
Abstract: In this paper, a new segmentation scheme for the white blood cells from microscopic images is proposed. This is based on the K-means clustering technique. The RGB test images are converted to the L*a*b color space, and then the two color machinery (a and b) are used as features to the K-means clustering algorithm. The success of image analysis depends on segmentation reliability. The accurate partition of the image into …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 1, Issue 2, 2015 · pp. 10–13 Read article
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CSPC: A New Approach for Edge Detection of Gray-Scale Images
Abstract: We can define an edge of an image as a set of connected pixels that creates boundaries of several objects in an image. Generally, Edge detection is a process of segmenting an image into regions of discontinuity. Edge detection takes a greater role in digital image processing as well as practical aspects of our life.Edges of an image can begenerated by implementingseveral edge detector mechanisms.In this paper, anew edge detectionmechanismthat …
Published in International Journal of Distributed Computing and Technology · Vol. 2, Issue 1, 2016 · pp. 1–6 Read article
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A Review of Different Iris Recognition Systems
Abstract: Recognition of a person based on the iris structure has become a trending authentication method. Iris recognition systems have many advantages as compared to other authentication methods such as accuracy, reliability and uniqueness and hence it is used in many applications. The main applications are, access control in laboratories and factories, identification for Automatic Teller Machines (ATMs), banks etc., border control in airports and harbors. This paper deals with the …
Published in International Journal of Analog Integrated Circuits · Vol. 4, Issue 2, 2018 · pp. 16–22 Read article
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Detection of Brain Tumor Using K-means Clustering Algorithm
Abstract: A brain tumor is a dangerous medical illness that, if not treated promptly, can be fatal. Therefore, it becomes essential to find the tumor early on in order to organize therapy as soon as possible. A brain tumor is the result of the growth of abnormal cells in the brain. Brain tumors come in many different forms. The majority of brain tumors are malignant (cancerous); however, some are benign (noncancerous). …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 9, Issue 2, 2023 · pp. 1–9 Read article
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Recognition of Vehicle Number Plate Using Mathematical Morphology and Neural Networks
Abstract: This paper presents a method for recognition of the vehicle number plate from the image using neural networks and mathematical morphology. The main theme is to use different morphological operations in such a way so that the number plate of the vehicle can be extracted efficiently. The technique makes the extraction of the plate independent of color, location and size of number plate. The proposed approach can be divided into …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 3, Issue 2, 2017 · pp. 1–4 Read article
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Enhancing Image Quality with Deep Learning Techniques for Restoration and Denoising
Abstract: Abstract: Clear and high-quality images have become more and more necessary in recent years due to the rapid development of computer vision-based autonomous systems, including autonomous driving, underwater robots, video surveillance, and medical imaging. However, real-world circumstances, such as inclement weather, underwater scenes, and moving cameras, can lead to poorer-quality photographs. These degradations, which include color distortions, noise, and blurring, hurt how well visual systems accomplish tasks like target tracking, …
Published in International Journal of Broadband Cellular Communication · Vol. 10, Issue 2, 2024 · pp. 1–6 Read article
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Deep Learning Approach Based Brain Tumor Detection
Abstract: The brain tumor is one of the most deadly disease which is of great concern and hence to detect and extract the effected tumor area in the brain from the MRI has lot of research potential. It is also a very difficult task to perform by the experts. The perfection of the vivisection depends on how much experienced the radiologist or the clinical expert is. So to overcome the wastage …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 8, Issue 1, 2022 · pp. 57–63 Read article
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A Simple and Fast Skull Stripping Technique for Brain MR Images
Abstract: Skull stripping is an important aspect of study in the field of Medical image processing. It eliminates the present non-cerebral tissues from the MR image to improve the speed and accuracy of the algorithm. An unsupervised double segmentation based method has been proposed for faster processing. Threshold values required for double segmentation are obtained using the Otsu algorithm. This method avoids the conventional Morphological Opening and Morphological Closing operations to …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 6, Issue 1, 2020 · pp. 1–4 Read article
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Image Denoising Using IBP n Filter
Abstract: Abstract The ultrasound images are blurred by the multiplicative noise that is the Speckle pattern. It decreases the contrast and resolution of ultrasound images those outcomes in weak interpretation of image characteristics. In several image processing mechanisms like segmentation, classification and pattern recognition the speckle is a significant part. The conventional methods calculate the computation of LBP on gradient. The limitation of this technique was that the LBP mechanism divide …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 4, Issue 2, 2018 · pp. 37–45 Read article
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Detection of Leaf Diseases Using Image Processing Techniques
Abstract: Agricultural field plays a vital role in the earning to feed ever growing population. The productivity of the crop depends on pest attack, disease, weather, etc. The disease in plants will affect the production of crops. Detecting diseases in plants through visualization is a traditional method which is not relevant. We are focusing on reliable, fast and accurate detection method that can be done using image processing techniques to monitor …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 5, Issue 2, 2019 · pp. 14–19 Read article