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23 articles for “texture segmentation”
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Texture Segmentation Using Multichannel Filtering And Kohonen’s Self Organizing Map
Abstract: The texture is very important cue in region based segmentation of images. Texture features play a very important role in computer vision and pattern recognition. Texture segmentation can be broken down into two areas, feature extraction and clustering. In this paper, we implement two stage of feature extraction technique using multichannel filter and Self Organizing Map (SOM). Firstly, we go through channel filters, also known as 2-D Gabor functions. The …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 3, Issue 3, 2012 · pp. 17–30 Read article
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Texture Based Segmentation of Remotely Sensed Images
Abstract: Texture based segmentation approach extracts homogeneous regions that have similar texture properties. The texture patterns make use of the gray scale relationship between the center pixel and its surrounding neighbors. In this paper, a novel method is proposed that encodes the spatial relationship between adjacent pairs of neighbors on either side of the center pixel including itself along the given directions in an image. The novelty of the proposed method …
Published in Journal of Remote Sensing & GIS · Vol. 11, Issue 2, 2020 · pp. 5–13 Read article
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A Similarity Analysis between Linear Multiracial Feature and Non-linear Multiscale Texture in Detection and Segmentation at Brain Tumor
Abstract: The panorama of the stochastic model, i.e., Random model, is called cancer. In that cancer contain benign and malign cells among that the vulnerable is rapid growth of malign cells lead to jeopardy. According to existing system the MRI fetches with multiresolution fractal (linear) model known as multi-fractional Brownian motion method but the flavor of proposed system may be interesting to keep contourlet transform and genetic algorithm for feature selection …
Published in Journal of Advances in Shell Programming · Vol. 7, Issue 1, 2020 · pp. 1–7 Read article
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Leaf Disease Classification Using Artificial Neural Networks and Decision Tree Classifier
Abstract: Most of the population in India depends on agriculture production. Diseases on plant cause a significant loss of nation’s economy. The Loss can be reduced by identifying the disease at the earlier stage. Leaves are the main indicator of diseases in a plant. Hence efficient automatic leaf disease identification system is the need for the current scenario. As it detects the diseases on leaf immediately after they appear, it prevents …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 5, Issue 1, 2018 · pp. 26–32 Read article
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Plant Disease Detection Using SVM
Abstract: AbstractDiseases in plants are responsible for major production and economic losses and also reduction in yield. Detection of plant disease through some automatic technique is beneficial as it reduces a large work of monitoring in big farms of crops, and at very early stage itself, it detects the symptoms of diseases. Detection on plant is very critical for defensible agriculture. It is very challenging to monitor the plant diseases physically. …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 4, Issue 3, 2017 · pp. 8–12 Read article
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Automated Thyroid Nodule Detection in Ultrasound Image using Optimal Neural Network Classifier
Abstract: Malignant thyroid nodule detection is an important issue in thyroid ultrasonography image processing. Literature reports many algorithms in this domain. This research aims to design optimal decision support system (DSS) for ultrasound thyroid nodule image characterization into benign and malignant classes. Thyroid nodule region is segmented to extract texture features from thyroid nodule ultrasound images acquired from 38 patients using gray level co-occurrence matrix (GLCM) and statistical properties. These features …
Published in Journal of Advancements in Robotics · Vol. 2, Issue 2, 2015 · pp. 15–25 Read article
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A Novel Feature Level Fusion Method for Classification of Remote Sensing Images
Abstract: Feature level fusion approach is utilized in this paper to classify remote sensing images. Texture features are extracted from panchromatic images using mixed Gabor filter (GB), fast gray level co-occurrence matrix (GLCM) and linear binary pattern (LBP). The resultant texture features are classified using nearest neighbor (k-NN) classification method. Spectral features are extracted from the MS image and segmented using over segmented k-means algorithm with novel initialization (OSKNI). Finally the …
Published in Journal of Remote Sensing & GIS · Vol. 10, Issue 1, 2019 · pp. 58–65 Read article
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Classification and Detection of Brain Tumor using Convolutional Neural Network
Abstract: Tumors are masses created when brain cells multiply uncontrollably. A brain tumor is the medical term for this condition. Brain tumors are a serious and aggressive disease that can lead to a reduced life expectancy. Developing a treatment plan is essential to raising a patient's standard of living. Tumors in different regions of the body are evaluated using a variety of imaging techniques, with MRI pictures being utilized mostly for …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 8–13 Read article
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Automatic Detection and Classification of Brain Tumor in Magnetic Resonance Images
Abstract: Brain tumor is one of the serious diseases that have caused death to many people in recent years. The complex structure of the brain and its main function associated with the central nervous system and its critical role in controlling most of the functions of the body make detection of tumor a challenging task. Many techniques have been presented in the medical field in order to detect brain tumor from …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 5, Issue 2, 2018 · pp. 34–40 Read article
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Different Image Processing Techniques to Detect Text from Natural Images: A Survey
Abstract: Texture analysis can provide very useful and vital information for content-based image analysis. Text recognition and analysis includes many applications such as: license plate recognition, sign detection as well translation, helping tourists and blind persons to understanding environment, drawing attention of a driver, content-based image search and so on. Locating text in case of variation in style, colour, as well as complex image background makes text reading from images more …
Published in Journal of Operating Systems Development & Trends · Vol. 1, Issue 3, 2014 · pp. 1–5 Read article
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Colour Based Segmentation of a Landsat Image Using K-Means Clustering Algorithm
Abstract: AbstractImage segmentation is one of the typical vintage subjects in image processing and it acts as a bulls-eye of the image processing technique. By definition, image segmentation means identifying the similar regions in the image; or in other words, identifying the homogenous pixels in the image and grouping all these pixels based on the homogeneity condition considered. This homogeneity condition can be like, colour, texture, size, compactness etc. It is …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 4, Issue 3, 2017 · pp. 31–38 Read article
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Nail Image Processing for Early Symptom Detection of Diseases based on Supervised Learning
Abstract: Digital Image Processing of human nail can be used for the prediction of various systemic and dermatological diseases. The proposed system – Nail Image Processing System using SVM (NIPS-S) helps us to create a model for the analysis of human nail and predict various diseases. The input to the proposed system is the Human Palm Image. The nail portion is segmented and a combination of nail color, shape and texture …
Published in Journal of Computer Technology & Applications · Vol. 8, Issue 3, 2017 · pp. 49–61 Read article
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Plant Leaf Sickness Recognition Using Image Processing
Abstract: This paper demonstrates the use of image processing techniques in detection of diseases in plants. The system which we have demonstrated in this technique is a software result for computerized detection and computing of the texture enumeration for the leaf diseases in plants. This processing system involves four major steps: (1) in this step we take an RGB image as input and it’s colour transformation structure is created, (2) in …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 2, 2016 · pp. 26–31 Read article
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AGRISMART: Crop and Soil Management System
Abstract: Agriculture has played a crucial role in developing countries where the majority of the rural population relies on it for their livelihoods. A finer-grade crop classification has become crucial in the context of precision agriculture. In recent years, the volume of open image data has grown significantly. This can be used in combination with machine learning techniques to classify crop types in the agricultural industry. The proposed crop species recognition …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 3, 2025 · pp. 50–55 Read article
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Face Aging Using Generative Adversarial Network
Abstract: This project addresses the challenge of predicting how a person may look in the future or how they appeared in the past using a single photograph. While existing methods mainly focus on altering texture, they often neglect changes in head shape that naturally occur during the aging process, limiting their effectiveness, especially when applied to images of children. To tackle this issue, a novel approach is introduced that employs a …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 41–52 Read article
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Refining Retinal Layer Segmentation in OCT Imaging with Advanced Techniques and Clinical Applications
Abstract: Segmenting retinal layers from Optical Coherence Tomography (OCT) pictures entails locating and separating different retinal layers to offer comprehensive anatomical and pathological information. Age-related macular degeneration, diabetic retinopathy, and glaucoma are among the retinal illnesses for which this procedure is crucial for diagnosis and follow-up. By utilizing preprocessing techniques to improve image quality and applying advanced algorithms—such as intensity-based, gradient-based, and texture-based methods—alongside deep learning approaches, clinicians can accurately measure …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 01–06 Read article
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Extraction of Retinal Features in Fundus Images for Glaucoma Diagnosis
Abstract: Glaucoma is a major cause for blindness, identified early by the structural changes of optic nerve head in the retina. Retinal image analysis is emerging as an important screening tool for prior detection of eye diseases. Glaucoma is a chronic eye disease in which damage to the optic nerve leads to progressive, irreversible vision loss and it is considered as second leading cause for blindness worldwide. In this research work, …
Published in Current Trends in Information Technology · Vol. 6, Issue 1, 2016 · pp. 21–28 Read article
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A Review on Thermodynamic Analysis of thermal Heat Dissipating Fins
Abstract: The Engine chamber is one of the essential motor components, that is exposed to extreme temperature varieties and thermal burdens. Balances are set on the outer layer of the chamber to improve the measure of Heat & mass transfer by convection. For thermal investigation of the motor chamber blades, it is more gainful to know the Heat & mass transfer dissemination inside the chamber. Present review has been done to …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 8, Issue 2, 2021 · pp. 13–21 Read article
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Image Preprocessing and Analysis on Eye Fundus Images Segmentation by Using Density Clustering Methods
Abstract: In order to do an automated evaluation of various retinal illnesses such as Diabetic retinopathy, Glaucoma, and Macular Edema, fundus images must be pre-processed first. For many reasons, it's difficult to accurately detect the optic disc. Many blood vessels cross the optic disc, making it difficult to discern the disc's boundaries in fundus images. Lesion regions in diabetic retinopathy look very much like an optic disc's colour and texture, so …
Published in Recent Trends in Sensor Research & Technology Read article
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Image Preprocessing And Analysis On Eye Fundus Images Segmentation By Using Density Clustering Methods
Abstract: Abstract: In order to do an automated evaluation of various retinal illnesses such as Diabetic retinopathy, Glaucoma, and Macular Edema, fundus images must be pre-processed first. For many reasons, it's difficult to accurately detect the optic disc. Many blood vessels cross the optic disc, making it difficult to discern the disc's boundaries in fundus images. Lesion regions in diabetic retinopathy look very much like an optic disc's colour and texture, …
Published in Recent Trends in Sensor Research & Technology · Vol. 8, Issue 3, 2021 · pp. 11–18 Read article