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128 articles for “image normalization”
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Hybrid HMM/ANN Models for Improving Offline Handwritten Text Recognition
Abstract: AbstractIn this approach, it proposes the use of hybrid Hidden Markov Model (HMM)/Artificial Neural Network (ANN) models for recognizing the unconstrained offline handwritten texts. Handwritten image normalization from a scanned image includes several steps, usually it begin with image cleaning, page skew correction, and line detection. For handwritten text line image several pre-processing steps to reduce variation in writing style are performed like slope and slant removal and character size …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 3, 2016 · pp. 16–23 Read article
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Alzheimer’s Disease Classification Based on Transfer Learning of New-CNN Model
Abstract: The long-term, irreversible brain disorder “Alzheimer’s disease (AD)” currently has no known cure. Nonetheless, current medications may impede their advancement. Globally, those over 65 are the primary population affected by Alzheimer’s disease. Accurate detection of this condition requires early diagnosis. Because there are so many people who come with an ailment, manual diagnosis by health specialists is laborious and prone to error. Early detection of AD is a difficult undertaking …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 · pp. 16–23 Read article
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Image Interpolation and Object Recognition Approach based on SAI Algorithm with Normalized Cross Correlation
Abstract: This paper mainly deals with producing quality of an image using soft-decision interpolation technique and also identifying the particular object in that image with the help of Normalized Cross Correlation. the use of image interpolation, to reserve spatial details. Identifying the missing pixels in an image one by one for many times, we are proposing the new technique, identifying missing pixels in a group. This new technique can be applied …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 1, Issue 1, 2014 · pp. 13–17 Read article
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Machine Learning Classification of Normal Versus Age-Related Macular Degeneration OCT Images
Abstract: The macula is a small area of the retina which is especially very important for good eyesight. The age related macular degeneration (AMD) is a type of visual impairment that can cause central vision blur or even loss of visionblindness or even loss of eyesight. AMD was a dangerous and progressing chronic disease which affects people over the age of 60. One of the most common symptoms of this condition …
Published in Journal of Control & Instrumentation · Vol. 13, Issue 3, 2022 · pp. 1–8 Read article
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Improved Face Recognition Rate Based on PCA and LDA Using Image Preprocessing Techniques
Abstract: Principal component analysis (PCA) and linear discriminant analysis (LDA) are two powerful tools utilized for dimensionality reduction and feature extraction in most of pattern recognition applications. PCA selects features important for class representation while LDA algorithm selects features that are most effective for class separability. This paper carries out a comparative study of the two important algorithms in the context of enhancement obtained using certain image preprocessing techniques. The implementation …
Published in Journal of Instrumentation Technology & Innovations · Vol. 5, Issue 2, 2015 · pp. 19–24 Read article
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Optical Character Recognition Using Back Propagation Neural Network
Abstract: This paper represents an Artificial Neural Network (ANN)-based approach for the recognition of English characters using feed-forward neural network. Noise has been considered as one of the major issues that degrades the performance of character recognition system. Our feed forward network has one input, one hidden, and one output layer. The entire recognition system is divided into two sections, namely training and recognition section. Both the sections include image acquisition, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 2, 2016 · pp. 11–18 Read article
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Classification of Ceramic Tiles Using Image Processing
Abstract: Normal 0 MicrosoftInternetExplorer4 In ceramic tile industry quality of tiles is very important. Once the manufacturing of tile is finished it has to be classified. At present this classification is doing manually but the human inspection may be effected by the external disturbances, sometimes angle of light also leads to the false judgment. This paper will give a solution to this problem. This paper deals with the Quality control of …
Published in Journal of Instrumentation Technology & Innovations · Vol. 2, Issue 2, 2012 · pp. 1–7 Read article
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U-Net Based Approach for Automated Brain Tumor Classification
Abstract: Brain tumor detection and identification play vital roles in diagnostic procedures in the field of medicine, with the conventional analysis of MRI images requiring a lot of time and also subject to variability. The proposed study involves the use of a CNN-U-Net based approach for brain tumor detection and identification automatically. The study uses a database of 3,064 contrast-enhanced T1-weighted MRI images from 233 patients with the tumors of meningioma, …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 Read article
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Estimation of Land Surface Temperature using Landsat Data: a Case Study of Agra City, India
Abstract: Land surface temperature (LST) is an important indicator for the study of climate change, urban environment, heat balance studies, hydrological and agricultural process, and urban land use and land cover as well as user input for climate models. Landsat data is utilized for the number of applications such as environment study, digester and resource management. Land surface temperate is estimated by the help of ArcGIS through Landsat 8 and 5 …
Published in Journal of Remote Sensing & GIS · Vol. 10, Issue 3, 2019 · pp. 48–57 Read article
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Trend analysis of Normalized Difference Vegetation Index using Landsat Satellite data: Study from in and Gondar town, North West Ethiopia
Abstract: Abstract This current research study presents the change detection method for the study of Satellite image supported on Normalized Difference Vegetation Index (NDVI). NDVI utilizes the Multi-Spectral remote sensing data method to determine Vegetation Index, land cover classification, vegetation, water bodies, bush land, agricultural area, thick forest and thin forest with few bands grouping of the remote sensed data. Land resources are easily understood by calculating their Normalized Difference Vegetation …
Published in Journal of Control & Instrumentation · Vol. 10, Issue 3, 2019 · pp. 25–33 Read article
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Performance Analysis of Segmentation using Thresholding Technique and K-means Clustering Techniques in Mammograms
Abstract: The main objective of the study is the attainment of proper segmentations of mammographic images which are taken from Mammographic Image Analysis Society (MIAS) digital mammogram database. In this study normal breast images and breast image with masses used as the standard input to the proposed system are taken from Mammographic Image Analysis Society (MIAS) digital mammogram database so as to be used in tasks such as to find micro …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 1, Issue 1, 2011 · pp. 115–121 Read article
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Comparative Analysis of Proposed FCM Clustering Integrated Enhanced Firefly-Optimized Algorithm (En-FAOFCM) for MR Image Segmentation and Performance Evaluation
Abstract: Image segmentation has a significant responsibility in diagnosis and treatment of diseases. To scan patients and determine the severity of certain injuries in hospitals, magnetic resonance imaging (MRI) method is normally used. This paper emphasizes on comparative study of segmentation techniques for segmenting MRI brain images. In this regard, to group the pixels of images in the intensity space, unsupervised clustering techniques are used. Here enhanced firefly algorithm is used …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 1, 2016 · pp. 32–44 Read article
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Deep Learning Based Detection and Classification of Brain Tumors Using MRI Images
Abstract: Brain tumor detection using magnetic resonance imaging (MRI) is a critical task in the early detection and treatment of brain tumors. Manual analysis of brain tumor detection using MRI is a tedious task that requires expertise in the field. Therefore, this study proposes a deep learning-based approach for brain tumor detection and classification using Convolutional Neural Networks (CNN). The proposed approach preprocesses the MRI image using normalization, resizing, and noise …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Brain Tumor Detection Using an Artificial Neural Network in MRI Images
Abstract: MRI is the widely used imaging technique in the biomedical field for the detection, diagnosis and evaluation of brain tumors. The large structural variability among brain tumor makes detection of a challenging problem. The medical problems are severe, if the tumor is detected at the later stage. Hence, diagnosis is necessary at the earliest. In this work, a neural network classifier is used for the detection of tumors from the …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 5, Issue 1, 2018 · pp. 14–22 Read article
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Urban Flood Hazard Modeling for Noida City
Abstract: This contemporary work unveils the usage of a new methodology to carry out an accurate hazard mapping of urban flood footprints. It is based on wetness transformation. It is a procedure of conversion of multi-spectral-bands into three dimensional feature space. The present study embraces conversion of thematic mapper (TM) imagery of Landsat to a three dimensional array; brightness, wetness and greenness, followed by the technique of change detection to locate …
Published in Journal of Remote Sensing & GIS · Vol. 7, Issue 1, 2016 · pp. 10–26 Read article
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Innovative CNN Strategies for Superior Handwritten Digit Recognition
Abstract: Handwritten digit recognition is a fundamental problem in the field of computer vision and machine learning with numerous applications, such as postal code recognition, bank check processing, and digitizing historical documents. Convolutional Neural Networks have demonstrated remarkable success in various image recognition tasks, making them a popular choice for digit recognition. In this study, we present an enhanced approach to handwritten digit recognition using CNNs. Handwritten digit recognition plays a …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 2, Issue 1, 2024 · pp. 27–34 Read article
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Automated Crop Disease Detection Using Convolutional Neural Networks
Abstract: Crop diseases contribute to major losses in agricultural production worldwide generating enormous economic costs. This study investigates the possibility of Convolutional Neural Networks (CNN) imaging techniques to auto-detect diseases associated with plants through image processing. A model was developed and trained on a publicly available plant disease dataset containing labeled images of several diseases. The CNN could classify various plant diseases with accuracy of 95%, precision of 92%, and recall …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article
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Advanced Deep Learning Techniques for Sickle Cell Anaemia Detection
Abstract: Sickle Cell Anemia (SCA) is a prevalent genetic blood disorder characterized by the presence of abnormal hemoglobin, resulting in the distinctive sickle shape of red blood cells. Timely and accurate identification of Sickle Cell Anemia (SCA) is essential for effective management and treatment. This study presents a new method that utilizes Convolutional Neural Networks (CNNs), a deep learning model particularly effective for image analysis. The process involves using microscopic images …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 3, 2024 · pp. 9–15 Read article
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Comparison of Performance of Haar Wavelet Transform on 3D-2D Multi-Sensor Face Images Using Simulation Model
Abstract: Human face has its own unique characteristics that are always considered to be the valid biometric feature for automation of security systems. A dedicated system doesn’t only require accurate algorithm but also it is required to be executed with a minimum span of time. In this literature, authors have stated and demonstrated a wavelet based feature space design mechanism from human faces and also analyzed the performance of execution for …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 3, Issue 1, 2015 · pp. 11–27 Read article
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Early Lung Cancer Prediction using deep Learning
Abstract: Lung cancer is a global killer because it’s often found late. Finding it early is key to treatment and survival so computer assisted diagnostics are essential. This research uses deep learning to spot early stage lung cancer from CT scans. We trained and fine-tuned three convolutional neural networks—ResNet50, Dense Net 201 and EfficientNet-B0—using transfer learning. We preprocessed the lung CT images by resizing, normalizing and augmenting them to enhance the …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 Read article