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305 articles for “image pre-processing”
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Farmer’s Pal
Abstract: Precision agriculture, characterized by data-driven decision-making, has transformed contemporary farming practices. To increase agricultural sustainability and efficiency, this abstract investigates the combination of sensor monitoring, machine learning, and picture processing. A network of sensors continuously collects vital environmental data, including temperature, humidity, rainfall, sunshine, soil moisture, and conductivity, for precision agriculture. By providing real-time insights, these sensors enable farmers to make informed choices about pest control, fertilization, and irrigation. This …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 19–31 Read article
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Car License Plate Detection and Recognition using Morphological Image Processing and Template Matching
Abstract: This study presents a robust method for vehicle number plate detection and identification. It mostly consists of three stages: plate extraction, plate number separation, and number recognition. Morphological operation is used to extract plate and numbers, whereas template matching is used to recognize the extracted number images. After that, it looks into a predefined dataset to decide if the number is licensed. Being independent of plate size, color and illumination …
Published in Journal of Computer Technology & Applications · Vol. 11, Issue 1, 2020 · pp. 21–27 Read article
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Smart Agriculture in India: Advancements in Image Processing for Automated Plant Disease Detection and Crop Analysis
Abstract: The adoption of image processing technologies in agriculture is emerging as a revolutionary method for tackling persistent challenges in the farming industry. These techniques are increasingly used for different tasks such as detecting plant diseases, assessing crop health, and predicting yields, especially in the framework of smart agriculture systems. This study paints a detailed picture of the latest progress in image processing techniques applied to automated disease detection and detailed …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 13–19 Read article
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Design and Development of Screw Detection System : A case study
Abstract: This study explores the design of a vision-based screw detection and orientation system for industrial automation, inspection, and robot disassembly. By integrating machine learning algorithms like region-based convolutional neural networks (R-CNN) with traditional image processing and impedance sensing, the system performs real-time screw presence detection, head type identification, and alignment. Three key technologies—deep learning classification, edge-based geometric analysis, and impedance verification—are integrated into a single modular system. The findings indicate …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 30–36 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
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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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Automated Headlight Intensity Controller and Speed Control in Vehicles
Abstract: AbstractHeadlight intensity of vehicles poses a great danger during night travel. The drivers of most vehicles use high bright beam while driving at night. This causes inconvenience for the person travelling from the opposite direction. Person experiences a sudden blaze for a short duration. When these headlights shine brightly, they cause a temporary blindness to a person, resulting in road accident during night. To avoid such incidents, we are designing …
Published in Journal Of Network security · Vol. 7, Issue 2, 2019 · pp. 1–5 Read article
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Automated Blood Cell Counting and Disease Identification Using Image Processing: Implications for Polymer Composite- Based Biomedical Diagnostic Devices
Abstract: Accurate quantification of blood cells is central to clinical decision-making and to the performance of emerging polymer composite–based diagnostic platforms. This work presents a cost-effective, image-processing pipeline for automated counting of red blood cells (including overlapping cells), white blood cells, and platelets from Leishman-stained peripheral blood smears, and articulates its relevance to polymer composite microfluidic and biosensor devices. Implemented in Python with OpenCV, the workflow performs grayscale conversion, median/Gaussian denoising, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 262–270 Read article
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Spatial variations of land surface temperature and its relationship with the type of land use/cover
Abstract: Environmental parameters are intricately interdependent and affect nearby and sometimes distant components. Environmental parameters become more important when dealing directly with humans. Land surface temperature (LST) is one of the environmental parameters that when it is related to the city as the main center of human gathering, it is referred to as urban heat island (UHI). Land use/ Land cover (LU/LC) is one of the important environmental parameters that affect …
Published in Journal of Geotechnical Engineering · Vol. 11, Issue 1, 2024 · pp. 1–16 Read article
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A Review on FPGA Parallel Architecture for Object Detection
Abstract: The main purpose in the case of present paper is to summarize the different parallel architecture techniques implemented on FPGA by which we can fulfil our requirement of object detection in image processing system. In image processing, it is difficult to find high precision and real time performance even in most powerful CPU. The various parallel architecture techniques can help in to give better performance and achieve high precision. This …
Published in Journal of VLSI Design Tools and Technology · Vol. 8, Issue 2, 2018 · pp. 42–48 Read article
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Crop Disease Prediction by Machine Learning
Abstract: The classification of Crop can be classified into several methods. The data set of crop leaf illnesses, notably Bacterial Leaf Blight disease (BLB), a crop leaf disease with significant outbreaks throughout Thailand, and Brown Spot Crop disease (BSR), is classified employing image classification in this study. Additionally, image processing technology is used for identifying different types of crop leaf disease. These algorithms include the Random Forest, Decision Tree, Gradient Boost, …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 21–25 Read article
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Driver Drowsiness Detection System Using Python, OpenCV and Raspberry Pi
Abstract: The number of accidents and deaths can be greatly decreased by using intelligent systems to prevent auto accidents. Human mistakes, such as drowsy driving, are one of the variables that significantly contribute to accidents. The system looks for symptoms of fatigue and sleepiness on a person's face while they are driving. It is based on an image processing technique. This project presents a way to analyze and anticipate driver drowsiness …
Published in Trends in Opto-electro & Optical Communication · Vol. 13, Issue 2, 2023 · pp. 6–15 Read article
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Smart Water Harvester
Abstract: Smart water harvester is a wiser use of Data Science in the optimization of rainwater harvesting, taking into account the forecast of precipitation and ideal catchment areas, and basically image processing using machine learning. In that respect, the system, via predictive algorithms like Random Forests, predicts the amount of rainfall by taking into consideration historical and real-time data, while Digital Elevation Models (DEM) and visualization methodologies of images make geographical …
Published in Journal of Water Resource Engineering and Management · Vol. 11, Issue 3, 2024 · pp. 1–7 Read article
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Study on Brain Tumor Detection Using Morphological Operations in MATLAB with Graphical User Interface (GUI)
Abstract: Brain tumor detection plays a crucial role in early diagnosis and effective treatment planning. This research presents a MATLAB-based Graphical User Interface (GUI) for Brain Tumor Detection, incorporating a comprehensive pipeline of image processing techniques. The GUI provides a user-friendly platform, empowering medical professionals to accurately and efficiently analyze MRI brain scans. The GUI begins with text removal to eliminate any textual artifacts that may be present in the MRI …
Published in International Journal of Radio Frequency Innovations · Vol. 1, Issue 1, 2023 · pp. 24–31 Read article
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Implementation of Image Processing Technique to Assess the Surface Free Energy of Asphalt Binder
Abstract: The adhesive properties of asphalt binder are considered as a major issue in the durability of the pavement. When asphalt cement does not match the standard specification required for paving work, one of the existing remedy processes is to implement modifiers to enhance the quality. Image processing technique can detect the variation in the adhesive properties through the assessment of surface free energy of the binder. In the present assessment, …
Published in Trends in Transport Engineering and Applications · Vol. 9, Issue 1, 2022 Read article
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Detectiverse: Advancing Supply Chain Efficiency with AI-Enhanced Screw Counting
Abstract: Accurate screw counting is essential in the manufacturing sector to ensure efficient inventory management and maintain quality control standards. The current manual counting method is prone to errors and lacks the ability to identify the source of missing screws. To address this challenge, we propose implementing an automated screw counting system at Indo Metal Tech in Ambattur, Chennai. This system would utilize advanced image processing and machine learning algorithms to …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 1, 2024 · pp. 21–26 Read article
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CNN-Based Wound Segmentation: A Review of Models and Performance Evaluation
Abstract: Deep learning, particularly convolutional neural networks (CNNs), has altered medical image processing by automating and precisely segmenting complex medical pictures. Wound segmentation, a critical application in automated wound assessment, is essential for wound size estimation, classification, and healing progress monitoring. This study presents a comprehensive review of CNN-based wound segmentation models, focusing on their architectures, methodologies, and performance on diverse datasets. Four deep learning models, including two U-Net variants (5-layer …
Published in Current Trends in Signal Processing · Vol. 15, Issue 1, 2025 · pp. 33–46 Read article
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Maintain Attendance Using Image Processing Technique
Abstract: Attendance tracking stands as a pivotal pillar in organizational management, bearing significant implications for operational efficiency, resource allocation, and fostering accountability. Traditional methodologies for attendance maintenance frequently exhibit deficiencies in terms of precision, security, and scalability, thus necessitating the exploration of avant-garde solutions. This research endeavors to introduce a pioneering approach to attendance upkeep, harnessing the prowess of image processing techniques synergized with artificial intelligence (AI) algorithms to surmount prevailing …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 2, 2024 · pp. 29–34 Read article
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Farming Forward: Integrating IoT, AI, and Image Processing for Sustainable Agriculture
Abstract: Farming Forward: Integrating IoT, AI, and Image Processing for Sustainable Agriculture" explores the convergence of cutting-edge technologies in revolutionizing traditional farming practices towards sustainability. This study investigates the integration of Internet of Things (IoT), Artificial Intelligence (AI), and Image Processing techniques in agricultural contexts, aiming to enhance efficiency, productivity, and environmental stewardship. Through a comprehensive review of recent advancements and case studies, this research elucidates the transformative potential of IoT-enabled …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 52–69 Read article