Feature Detection and Matching
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Evaluation of Similarity Measures for Template Matching
Image matching is a critical process in various photogrammetry, computer vision and remote sensing applications such as image registration, 3D model reconstruction, change detection, image fusion, pattern recognition, autonomous navigation, and digital elevation model (DEM) generation and orientation. The primary goal of the image matching process is to establish the correspondence between two ...
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In this paper two novel steganalysis methods is presented based on co-occurrence matrix of an image. It is shown that by using features extracted from this matrix, we can differentiate between cover and stego images. These features include energy, entropy, contrast, inverse difference moment, maximum probability and correlation. We use SVM classification for separation of cover and stego imag...
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Image feature detection and matching is a fundamental task in image processing and machine vision. In this paper we present novel methods for feature detection and matching. We have used edge points and their accumulated curvature information for feature detection. The detected features are then matched using a new method called “fuzzy-edge based feature matching”. To increase the speed of matc...
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Image registration is a crucial step in most image processing tasks for which the final result is achieved from a combination of various resources. In general, the majority of registration methods consist of the following four steps: feature extraction, feature matching, transform modeling, and finally image resampling. As the accuracy of a registration process is highly dependent to the fe...
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Despite the semantic criteria, geometric criteria have different performances on polygon feature matching in different vector datasets. By using these criteria for measuring the similarity of two polygons in all matchings, the same results would not have been obtained. To achieve the best matching results, the determination of optimal geometric criteria for each dataset is considered necessary....
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Due to the rise of technology, the possibility of fraud in different areas such as banking has been increased. Credit card fraud is a crucial problem in banking and its danger is over increasing. This paper proposes an advanced data mining method, considering both feature selection and decision cost for accuracy enhancement of credit card fraud detection. After selecting the best and most effec...
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