Feature descriptors
A Fast Interest Points Feature Descriptors Algorithm for Mobile Image Retrieval Applications
... (IPs) feature descriptors from query that could overcome image capturing problems: noise, rotation, and cropping ...IPs descriptors on an adequate image ...
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Appearance-based odometry and mapping with feature descriptors for underwater robots
... each feature is associated with a scale and an orientation ...the feature according to the assigned orientation, thus achieving invari- ance of the descriptor to ...
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Combinations of Feature Descriptors for Texture Image Classification
... advanced feature descriptors to improve the accuracy of texture classi- fication systems, and there are many examples of successful ...standard feature extraction techniques to the Brodatz, UIUCTex ...
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A Survey on Image Feature Descriptors
... binary descriptors is that each bit in the descriptor is independent and the Hamming distance can be used as similarity measure instead of, ...binary feature descriptors are (1) Binary Robust ...
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Performance Evaluation of Face Recognition based on Multiple Feature Descriptors using Euclidean Distance Classifier
... ) to recognize the face and is implemented in a smart phone with Android OS. The input facial image is captured using Smartphone and Local Binary Pattern is used for extracting the features of facial image. Euclidean ...
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A Novel Image Classification Method Using Texture Feature Descriptors
... Nowadays images are broadly utilized because of its visual representation. Classification of the objects is an easy task for humanity, but its challenging task for the machine. The image data can take many forms, such as ...
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Radiomics in Brain Tumor: Image Assessment, Quantitative Feature Descriptors, and Machine Learning Approaches
... Extracting large-scale radiomic features from a variety of imaging arrays creates a rich data base containing clinically relevant infor- mation. Both computational and biologically inspired feature de- scriptors ...
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Deep rule based classifier with human level performance and characteristics
... the feature descriptors that are employed in the DRB classifier to make it ...self-contained. Feature extraction can be viewed as a projection from the original images to a feature space that ...
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Mobile Visual Search: A Low Transmission Overhead Framework Based on Vocabulary Decomposition
... sample descriptors extracted from images in the ...local feature descriptors extracted from the query image as the query ...the descriptors from the client, the server encode them into visual ...
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FORENSIC SKETCH-PHOTO MATCHING USING SIFT- MLBP- LFDA
... In LFDA framework [7], the following feature descriptors are used i.e. scale invariant feature transform (SIFT) and multiscale local binary pattern (MLBP).In its original formulation, the SIFT ...
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ANALYSIS OF KEY-POINT METHOD AND BLOCK-BASED METHOD FOR TAMPER DETECTION
... two feature descriptors is interpreted as a cue for a duplicated ...similar feature vectors. In lexicographic sorting a matrix of feature vectors is created so that each feature vector ...
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Dimensionality Reduction for Handwritten Digit Recognition
... dimensional feature sets with dimensionality reduction ...popular feature descriptors, Histogram of Oriented Gradients (HOG) and Gabor filters, are used to generate the feature ...the ...
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Feature exploration for biometric recognition using millimetre wave body images
... It is known that fusing complementary information would lead to a better performance of the system. To this aim, we propose for future work the fusion of some of the feature descriptors explained in this ...
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Accurate pedestrian localization in overhead depth images via Height-Augmented HOG
... Gradients-like feature descriptors, neural networks, data augmentation and custom data annotation strategies, this work contributes a robust and scalable machine learning-based localization algorithm, which ...
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Indian Currency Recognition Based on ORB
... This phase consists of the learning process in recognition. The training phase contains all pre-processing mechanism which extracts the information from the input image. It involves image resizing followed by image ...
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Feature Selection Used for Retreving and to Classifying Images
... Over the last years new proposals have emerged in image classification research that uses the BoW model for image representation. This model was used in text retrieval initially . BoW is based on regions and points of ...
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On Image Retrieval using Salient Regions with Vector Spaces and Latent Semantics
... and feature vectors were generated about each salient region in all the training ...these feature descriptors was then performed using the batch k-means clustering algorithm with random start points ...
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Salient Region Filtering For Background Subtraction
... The method begins with the detection of salient regions in a collection of background images. Since large numbers of salient regions may typically be detected in a single image, a random sample of salient regions are ...
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Face Spoof Detection Using Naive Bayes Classifier
... In this work we present a face spoof detection technique in which the spoof attacks by an impostor are detected by naive bayes classification approach. Real Images are fed to the training database and spoofed images are ...
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Experimental Evaluation of the Performance of Local Shape Descriptors for the Classification of 3D Data in Precision Farming
... In this work, we concentrate on the classification of points into different plant organs, like stalks, leaves or berries. Based on this, it is possible to estimate yield or reconstruct the plant organs for the final ...
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