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18 articles for “Wavelet based Feature Extraction”
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Retina Recognition System Using Wavelet based Neural Network Algorithm
Abstract: This paper presents an approach of wavelet feature-based retina recognition system using back-propagation learning neural network algorithm. After acquiring the retinal image, at first vessels were segmented from the image. Then the feature extraction was carried out by analyzing the segmented retinal image using multiresolution analysis through the wavelet-based approach. Then extracted features were fed to the back-propagation learning neural network algorithm to create the learned template which was used …
Published in Current Trends in Signal Processing · Vol. 5, Issue 2, 2015 · pp. 35–39 Read article
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Bearing Fault Diagnosis Using ANN and SVM with the Help of Wavelet Transform Based Features
Abstract: Many researchers use vibration signals as fault characteristics of any rotating bearing for fault detection and use various optimization techniques available for fault of bearing classification. The method of fault classification uses few neural network (NN) geometry and parameters necessary for the formulation. There is no derived formulation which can be used to select the optimal values for the network parameters. The parameters which are required to be calculated, impacts …
Published in Recent Trends in Electronics Communication Systems · Vol. 4, Issue 2, 2017 · pp. 26–34 Read article
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Fault Identification by Wavelet Feature Extraction in Self Aligning Rolling Element Bearings Using Neural Networks
Abstract: This paper aims to present a comparison of different individual defects in self aligning ball bearings by the use of statistical tools and machine learning techniques like artificial neural network (ANN). The results generated are analyzed, and more realistic conformance to the theoretical observations has been drawn. Vibration analysis of a fault affected component gives a good understanding of machine diagnostics. Inner race and outer race defects have been studied …
Published in Trends in Mechanical Engineering & Technology · Vol. 7, Issue 2, 2017 · pp. 11–17 Read article
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Pair of Retina Recognition System Using Hopfield Neural Network Algorithm
Abstract: process of pair of retina recognition system using feature fusion method has been proposed in this paper. Left and right retinal images of human have been used for the inputs of this retinal recognition system. Wavelet based retinal image pre-processing technique has been applied to process the retina images. After extracting the features from the left and right retinal images, features are concatenated using feature fusion technique. Principal Component Analysis …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 2, 2015 · pp. 41–45 Read article
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Study of ECG Signal Features Extraction using Wavelet Transform: A Review
Abstract: QRS-complex detection is used for analysis of ECG signal. ECG gives the information about electrical activity of the heart Since an ECG is a non-stationary signal and consists of various types of noise such as baseline wander, power line interference and muscle noise. To eliminate such types of noise wavelet transform is used. Mother wavelet is widely used to extract information from these types of signal by denoising. This paper …
Published in Current Trends in Signal Processing · Vol. 4, Issue 2, 2014 · pp. 1–6 Read article
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A Novel Approach to Reduce Image Retrieval Problem Using Gabor Transform, Wavelet Transform and Euclidean Distance Measure
Abstract: In the processing of image, pattern recognition and computer vision, the image retrieval is a most famous research area. Our paper presents a new method in CBIR through merging the low level feature i.e. texture, color and shape features. At first, we transform the color space from RGB model to HSV model, and then extract color histogram to form color feature vector. CBIR is the process where search of image …
Published in E-Commerce for Future & Trends · Vol. 3, Issue 1, 2016 · pp. 10–15 Read article
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Image Processing Based Analysis of Fundus Images for Glaucoma Detection
Abstract: Precise and prompt identification of glaucoma is essential for its treatment. Fundus images provide important information, which shall be extracted using carefully designed image processing algorithms. The paper discusses a methodology for automatic detection of glaucoma from fundus images. The technique makes use of an elaborate image segmentation process, wavelet decomposition for feature selection and a proven classification model.Keywords: Glaucoma, fundus image, discrete wavelet transform, SVM classifierCite this ArticleShibina M.P, …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 5, Issue 1, 2018 · pp. 33–39 Read article
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Entropy Analysis Based Differential Evolution Approach for Emotion Classification for EEG
Abstract: Electroencephalography (EEG) signal processing is having its significance in various applications related to the emotion recognition and classification. The behavior monitoring, behavior class identification, emotion class identification are the major aspects for classification of EEG signal. In this paper, a feature adaptive differential evolution (DE) approach is defined to perform emotion classification. In this work, we used discrete wavelet transform (DWT), for extracting the statistical features from the EEG signal …
Published in Current Trends in Signal Processing · Vol. 5, Issue 3, 2015 · pp. 15–22 Read article
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A Novel Approach of Medical Image Fusion using Wavelet Transforms
Abstract: Image processing applications have been growing rapidly in real world. The term fusion means an approach to extract the useful information from several modalities. Image fusion (IF) is used to integrate the complementary information obtained from multisensor, multiview and/or multitemporal and get an image of more information and the quality of which cannot be achieved from any individual image. Different fusion algorithms are useful in many applications like medical diagnosis …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 5, Issue 1, 2018 · pp. 18–25 Read article
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An Evolution of the Pixel Embedding Techniques in Image Based Adaptive Steganography
Abstract: The word “Steganography” was basically derived from the Greek words with the meaning “covered writing.” This paper presents some of the main adaptive image steganography approaches. Many algorithms have been presented; in almost all the algorithms the approach is to embed the secret data in the images. Here we are discussing about adaptive steganography which is based upon spatial domain and frequency domain with an additional layer of mathematical model. …
Published in Journal of Web Engineering & Technology · Vol. 1, Issue 1, 2014 · pp. 1–18 Read article
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Artificial Neural Network-Based Multifocus Image Fusion
Abstract: Fusion of multiple images is needed for combining information contained in images obtained using different imaging devices or different camera settings. Due to the physics of optical lenses present in these devices, it is difficult to capture an image that has all the relevant objects well in focus. Thus, artificial neural network (ANN)-based multifocus image fusion method in YCbCr color space is proposed. Input images are first mapped from RGB …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 3, 2018 · pp. 16–23 Read article
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Visual Features based Paddy Leaf Disease Recognition, its Severity Detection and Remedy Prediction using K-means Clustering and AdaBoost
Abstract: AbstractAgriculture is a vital part of an economy. Paddy is one of the main food crops which play a major role in agricultural field. The gross national income of a country depends on paddy cultivation. But the production of paddy is damaged due to different types of paddy leaf diseases. Generally, farmers and agricultural experts identify diseases manually which is very ineffective and time consuming. So effective recognition, severity detection, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 7, Issue 3, 2020 · pp. 41–52 Read article
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An Exploration on Data Mining for Face Detection based on Real time Face Tracking
Abstract: AbstractData mining has been extensively used to gather meaningful information and to improve the significant relationship for the variables warehoused in large data stores. Machine learning provides the technical basis of data mining. Automatic face recognition research which try to give the computer ability to recognize face to distinguish characters. As a key technology of biometrics face recognition technologies, in public security, information security, financial, and other fields has potential …
Published in Journal of Computer Technology & Applications · Vol. 5, Issue 3, 2014 · pp. 46–51 Read article
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Multi-Parameter Biomedical Sensor-Based Mental State Classification Using EEG And Deep Learning Techniques
Abstract: With mental health concerns becoming increasingly widespread, there is a strong need for systems that can monitor conditions like stress, anxiety, and fatigue in a continuous and non- invasive manner. This research proposes a novel multi-parameter biomedical sensing framework for mental state classification by integrating electroencephalography (EEG) signals with physiological parameters, including body temperature acquired using LM35 sensors, heart rate from pulse sensors, and blood oxygen saturation (SpO₂) measurements. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 · pp. 1–8 Read article
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LBP-HOG-Statistical-Wavelet Transform Feature Based MCA Classifier
Abstract: Face recognition systems use computer algorithms choose specific, recognizable features on a person’s face. With a mathematical representation, the information is compared to data on other faces acquired in a face recognition database. The distance between the eyes or the shape of the chin are two examples of these characteristics. The job of matching several facial modes, such as visible and near infrared images, is known as heterogeneous face recognition. …
Published in Trends in Opto-electro & Optical Communication · Vol. 12, Issue 2, 2022 · pp. 19–30 Read article
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ECG De-noising Techniques and Optimal Feature Selection Using Principle Component Analysis
Abstract: AbstractECG (Electrocardiography) is used to record and determine the condition of the heart. This paper provides an overview of various ECG de-noising techniques that are used to eliminate different type of noises; therefore, noise reduction procedure to be performed to eliminate different type of noises such as baseline wander, dc offset and high frequency interference, and then the pre-processed signal is used to extract features from the ECG signal. This …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 5, Issue 1, 2018 · pp. 14–20 Read article
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Power Quality Monitoring in Wind Solar Hybrid System
Abstract: With the development of new functionalities, solar and wind energy based hybrid systems are upcoming energy source with higher efficiency. Solar and wind energy being naturally available in abundance and non-polluting, is one of the most promising sources. Due to the development of modern power electronic devices, the power quality of wind solar hybrid system gets affected. Hence, due to the increasing usage of sensitive electronic equipments in wind solar …
Published in Journal of Power Electronics and Power Systems · Vol. 8, Issue 1, 2018 · pp. 16–23 Read article
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Bearing Defect Diagnosis: An Approach for Manufacturing Industries Using Wavelet Transform Based Features
Abstract: To maintain reliability in the manufacturing units, industries have concentrated their attention on the condition based maintenance. Fault detection and diagnosis are the two of three condition based maintenance mainstays. Bearing is one of the most important and essential components of the rotating machines. Hence, the researchers have shown their interest in bearing fault detection and diagnosis from the last few years. They mainly use bearing vibration as fault characteristics …
Published in Journal of Microelectronics and Solid State Devices · Vol. 4, Issue 1, 2017 · pp. 15–21 Read article