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216 articles for “Features extraction and Detection”
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Rotation Invariant Copy-Move Image Forgery Detection Using a Method Based on Fuzzy-Zernike Moments
Abstract: AbstractWithout leaving any visual clue, digital images are easy to manipulate due to the availability of countless editing software packages. Any image manipulation can become a forgery. Copymove forgery is a very common method of creating forge images by copying some part of the image and pastes it on the same image. In this paper, we propose a copy-move digital image forgery detection method using Fuzzy-Zernike Moments. The proposed method …
Published in Journal of Computer Technology & Applications · Vol. 7, Issue 2, 2016 · pp. 58–68 Read article
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Retina Recognition System using PCA-based Discrete Hidden Markov Model
Abstract: In this paper, a unique approach of retina recognition system has been proposed. Principal component analysis based dimensionality reduction technique has been used here and discrete hidden Markov model (DHMM) has been applied to classify the retinal images. The retinal images are taken from DRIVE retina database. Then some image pre-processing techniques such as image scaling, median filtering-based noise reduction and edge-detection techniques have been used to ready the retinal …
Published in Journal Of Network security · Vol. 3, Issue 1, 2015 · pp. 28–32 Read article
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Multi-Layer Perceptron Neural Network Based Person Identification Using Appearance Based Facial Feature
Abstract: This paper deals with secure person identification system using Back-Propagation learning neural network algorithm where appearance based facial feature and Principal Component Analysis based dimensionality reduction technique have been used. To extract the appearance based facial features, Viola-Jones method has used as a face detector, Stam’s method of Active Shape Model has applied for detecting the facial edges and image pre-processing method has used for eliminating the background noises. For …
Published in Current Trends in Signal Processing · Vol. 4, Issue 1, 2014 · pp. 26–34 Read article
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CNN-Based Diagnosis of Skin Cancer from Dermoscopic Images
Abstract: Skin cancer has become one of the diseases widely spread over the globe, with melanoma becoming a severe threat to one’s health. Detection of such diseases at the initial stage saves an individual from drastic damage. Using a Convolutional Neural Network (CNN) for detecting skin cancer through image classification as benign or malignant provides significant support to dermatological practice and reduces dependence solely on subjective visual examination. Dermatologists often face …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 1, 2026 · pp. 37–42 Read article
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Performance Evaluation of Segmentation Algorithms for Apple Fruit Grading
Abstract: For supplying high-quality food products within a short time, automated grading of fruits is getting special attention. Fruit grading technique will grade the fruits using their shapes, color and outer look. This emphasizes the necessity of image segmentation which extracts important features from an image. This paper consists of analysis of different segmentation algorithms for detecting damage part of fruit. Marker-based watershed algorithm uses internal and external markers to locate …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 1, Issue 2, 2014 · pp. 34–40 Read article
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A Review of Automated Pomegranate Disease Detection and Classification Using Machine Learning
Abstract: The abstract outlines a research study focused on developing an automated system for detecting and classifying diseases that affect pomegranate fruits. Pomegranates, like many other crops, are vulnerable to several types of diseases that appear as visible colored spots on the fruit’s surface. These visible symptoms, such as lesions or discoloration, can significantly impact the fruit’s quality, market value, and yield. Therefore, timely and accurate identification of such diseases is …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 01–13 Read article
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Performance Evaluation of PCA Based Back Propagation over PCA Based Euclidian Distance for Video Images
Abstract: Key frame selection aims at reducing amount of data and retrieve information desired from a video. Video summarization aims at reducing the amount of data in order to retrieve information from a video. In this paper, we present an innovative approach for key frame selection; and a face detection and recognition from video sequence. For face detection from video, first we select the key frames and then detect multiple faces …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 1, 2016 · pp. 24–31 Read article
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Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
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Real-world Pothole Detection Using Image Processing and Deep Learning Convolutional Neural Network Model
Abstract: Potholes are a major problem of concern in many parts of the cities across the country. Road accidents are one of the causes that significantly affect humanity and result in damage to vehicles and road surface. Potholes are dangerous for pedestrians who walk along the road and vehicular traffic on busy roads. Road accidents are caused due to improper maintenance of roads, and it is imperative to attend to such …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 3, 2023 · pp. 95–103 Read article
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Deep Learning for Traffic Sign Recognition in Autonomous Vehicles: Challenges, Trends and Future Directions
Abstract: Traffic Sign Recognition (TSR) serves as a fundamental task in the domain of autonomous vehicles (AVs), enabling systems to detect, classify, and respond to road signs with the level of accuracy and speed required for safe navigation. As AV technology continues to evolve, the role of intelligent TSR systems has become increasingly vital. Traditional computer vision techniques, while foundational, often fall short under challenging real-world conditions such as poor lighting, …
Published in Journal of Advancements in Robotics · Vol. 13, Issue 2, 2026 · pp. 1–7 Read article
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Network Intrusion Detection System Using Decision Tree
Abstract: This paper presents a novel approach to network intrusion detection systems (NIDS) using advanced decision tree algorithms to address critical limitations in existing IDS solutions. Traditional IDSs often struggle with high false positive and negative rates, lack of scalability, and poor interpretability. Our proposed IDS leverages decision trees to enhance detection accuracy, interpretability, and scalability, thereby improving network security. Decision trees are chosen for their adaptive learning capabilities, transparent decision-making …
Published in Journal Of Network security · Vol. 12, Issue 2, 2024 · pp. 22–33 Read article
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Advancement in Image Classification: Media Player Control Using Hand Gestures
Abstract: We explore the development of picture categorization methods in this paper, with an emphasis on how they are used to manipulate media players with hand gestures. Our investigation focuses on the development of machine learning techniques, particularly on supporting vector machines (SVM) and convolutional neural networks (CNN). SVMs are used to identify and authenticate people from digital photos or video clips, but CNNs are great at face detection, which is …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 1–10 Read article
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Artificial Intelligence in Image Recognition: Context of Machine Vision
Abstract: The machine learning discipline is as old as decades, but some problems such as image recognition, location detection, image classification, image generation, speech recognition, and natural language processing cannot be solved. Image classification studies are another basic, most classic and essential line of research in deep learning. Computer intelligent recognition of the images technology has enabled a gradual reaction (updating) to foreign measurement trends, which promotes advancement of different areas …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 01–06 Read article
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Image Processing Techniques for Detecting and Classification of Leaf Diseases
Abstract: Plants are the way to make a living. From the factors of our daily life to breathing we are totally dependent on plants. Therefore, plant care must be proper. Plant diseases involve, of instance, algae, bacteria, and viruses. Several researchers have to classify plant diseases but it is time consuming to manually identify them. Image processing techniques are used to detect various diseases of the plant. There are several steps …
Published in Trends in Opto-electro & Optical Communication · Vol. 11, Issue 2, 2021 · pp. 1–6 Read article
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An Approach to Develop Secure Ear Biometric System
Abstract: Biometrics is now the significant identification process for security system. The futureof biometrics is surely leads to a system because the acquisition process for biometricsis very simple. Ear biometrics has an important role on biometrics system. Because it isa passive biometrics system which means that the user does not have to take active partin the whole process. The most interesting human anatomical parts for such passive,physiological biometrics systems based on …
Published in Journal Of Network security · Vol. 2, Issue 1, 2014 · pp. 1–6 Read article
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Early Detection of Alzheimer’s Disease Using Machine Learning Techniques
Abstract: Alzheimer's Disease (AD) is a progressive neurodegenerative condition impacting a large global population. Detecting AD early is critical for timely intervention and effective management. Conventional diagnostic approaches involve cognitive assessments and neuroimaging, which are often lengthy, costly, and prone to human error. In this paper, we propose a novel approach for early detection of AD using machine learning techniques applied to multimodal data, including neuroimaging, cognitive assessments, and biomarkers. Our …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 32–43 Read article
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Real-Time Deepfake Detection in Video Conferencing Systems
Abstract: Deepfake technology presents non-exemplary threats to video conferencing platforms, enabling advanced fraud, impression and misinformation campaigns worth billions annually. Current detection methods either exhibit latencies exceeding 100ms or rely on server-side cloud processing, raising privacy concerns. This paper presents DeepConfGuard, a lightweight hybrid architecture combining MobileNetV2 for spatial feature extraction, a bidirectional LSTM with attention for temporal modelling, and EfficientNetV2 for refinement. It reaches 94.8% accuracy with 85 ms end‑to‑end …
Published in International Journal of Electronics Automation · Vol. 4, Issue 2, 2026 Read article
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FACE EMOTION RECOGNITION TO DETECT DEPRESSION
Abstract: In the current competitive world, one of the most familiar and grave mental illness we encounter in humans is Depression also called as major depression or major depressive disorder. It makes you feel depressed and disinterested all the time, which has a bad impact on your thoughts and behaviour. Thus affecting not only the victim but also people associated with them, such as family, friends and society. If not treated …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 1–14 Read article
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Applying Text Analysis Methods for Emotion Recognition
Abstract: This article presents a comprehensive study of sentiment analysis, a vital task in the realms of natural language processing (NLP) and artificial intelligence (AI). Sentiment analysis involves the extraction and classification of subjective information from textual data, determining whether the sentiment expressed is positive or negative. This paper investigates different approaches and methodologies used in sentiment analysis, encompassing machine learning models as well. Additionally, it discusses the challenges faced in …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 11, Issue 2, 2024 · pp. 12–22 Read article
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Baggage Detection and Recognition Using Local Tri-Directional Pattern
Abstract: Nowadays, pattern-based image retrieval algorithms are gaining popularity just because of their uniqueness. There are several issues in the previously proposed systems. The proposed system resolves issues highlighted in the literature. Our proposed system is tested on two image datasets ILIDS and PETS 2006. LTDP provides good results as compared to LBP in baggage detection on two classes that either bag is present or not in an image because LTDP …
Published in International Journal of Mobile Computing Technology · Vol. 1, Issue 1, 2023 · pp. 8–17 Read article