Results 1 - 10 of 91,215

Optimization of Texture Feature Extraction Algorithm

by Tuan Anh Pham, Tuan Anh Pham , 2010
"... Texture, the pattern of information or arrangement of the structure found in an image, is an important feature of many image types. In a general sense, texture refers to surface characteristics and ap-pearance of an object given by the size, shape, density, arrange-ment, proportion of its elementary ..."
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and texture features using Cell Broadband Engine Architec-ture (Cell Processor). Experimental results show that our parallel approach reduces impressively the execution time for the GLCM texture feature extraction algorithm.

Best-Bases Feature Extraction Algorithms for

by Classification Of Hyperspectral, Shailesh Kumar, Joydeep Ghosh, Melba M. Crawford - IEEE Trans. Geoscience and Remote Sensing , 2001
"... Due to advances in sensor technology, it is now possible to acquire hyperspectral data simultaneously in hundreds of bands. Algorithms that both reduce the dimensionality of the data sets and handle highly correlated bands are required to exploit the information in these data sets effectively. We pr ..."
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propose a set of best-bases feature extraction algorithms that are simple, fast, and highly effective for classification of hyperspectral data. These techniques intelligently combine subsets of adjacent bands into a smaller number of features. Both top-down and bottom-up algorithms are proposed. The top

Dynamic Integration of Explicit Feature Extraction Algorithms

by Olcay Guldogan, Esin Guldogan, Serkan Kiranyaz, Kerem Caglar, Moncef Gabbouj - Into MUVIS Framework”, Proc. Finnish Signal Processing Symposium, FINSIG 2003 , 2003
"... In this paper, we present an integration scheme designed in a content-based multimedia indexing and retrieval framework (MUVIS) for independent feature extraction algorithms. We introduce the general structure of the framework, and describe the interface, the instructions and the conditions for inte ..."
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In this paper, we present an integration scheme designed in a content-based multimedia indexing and retrieval framework (MUVIS) for independent feature extraction algorithms. We introduce the general structure of the framework, and describe the interface, the instructions and the conditions

Analysis of Acoustic Feature Extraction Algorithms in Noisy Environments

by Weiyang Cai
"... I would like to express my greatest gratitude to the people who have helped and supported me. First, I would like to thank Professor Wendi Heinzelman for her continuous guidance and invaluable advice on my thesis. Many thanks to my parents for their undivided support and encouragement. I would also ..."
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like to thank Na Yang and He Ba from the Wireless Communication and Networking Group for providing advice on my thesis. This research was part of the Bridge project, which was supported by funding from National Institute of Health NICHD (Grant R01 HD060789).iv Acoustic feature extraction algorithms

A Novel Feature Extraction Algorithm for

by David Lindgren, David Lindgren , 2003
"... A linear feature extraction technique for asymmetric distributions is introduced, the asymmetric class projection (ACP). By asymmetric clas-si cation is understood discrimination among distributions with dierent covariance matrices. Two distributions with unequal covariance matrices do not in genera ..."
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A linear feature extraction technique for asymmetric distributions is introduced, the asymmetric class projection (ACP). By asymmetric clas-si cation is understood discrimination among distributions with dierent covariance matrices. Two distributions with unequal covariance matrices do

A RELIEF Based Feature Extraction Algorithm

by Yijun SUN, Dapeng WU
"... RELIEF is considered one of the most successful algorithms for assessing the quality of features due to its simplicity and effectiveness. It has been recently proved that RELIEF is an online algorithm that solves a convex optimization problem with a marginbased objective function. Starting from this ..."
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this mathematical interpretation, we propose a novel feature extraction algorithm, referred to as LFE, as a natural generalization of RELIEF. LFE collects discriminant information through local learning, and is solved as an eigenvalue decomposition problem with a closed-form solution. A fast implementation is also

A Direct Evolutionary Feature Extraction Algorithm for Classifying

by Qijun Zhao, David Zhang, Hongtao Lu - High Dimensional Data,” American Association for Artificial Intelligence 2006 , 2006
"... Among various feature extraction algorithms, those based on genetic algorithms are promising owing to their potential parallelizability and possible applications in large scale and high dimensional data classification. However, existing genetic algorithm based feature ex-traction algorithms are eith ..."
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Among various feature extraction algorithms, those based on genetic algorithms are promising owing to their potential parallelizability and possible applications in large scale and high dimensional data classification. However, existing genetic algorithm based feature ex-traction algorithms

A Robust Feature Extraction Algorithm for Audio Fingerprinting

by Jianping Chen, Tiejun Huang
"... Abstract. In this paper, we present a new feature extraction algorithm which can generate robust and reliable feature in a fingerprint system. This algorithm is referred to as weighted ASF (WASF). The feature in our algorithm is extracted based on a MPEG-7 descriptor-Audio Spectrum Flatness (ASF) an ..."
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Abstract. In this paper, we present a new feature extraction algorithm which can generate robust and reliable feature in a fingerprint system. This algorithm is referred to as weighted ASF (WASF). The feature in our algorithm is extracted based on a MPEG-7 descriptor-Audio Spectrum Flatness (ASF

On image matrix based feature extraction algorithms

by Liwei Wang, Xiao Wang, Jufu Feng - IEEE Trans. Syst., Man, Cybern. B, Cybern , 2006
"... (LDA) are two important feature extraction methods and have been widely applied in a variety of areas. A limitation of PCA and LDA is that when dealing with image data, the image matrices must be first transformed into vectors, which are usually of very high dimensionality. This causes expensive com ..."
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the computational effort and the possibility of singularity in feature extraction. In this paper, we show that these matrices based 2D algorithms are equivalent to special cases of image block based feature extraction, i.e. partition each image into several blocks and perform standard PCA or LDA on the aggregate

FEATURES EXTRACTION ALGORITHM FROM SGML FOR CLASSIFICATION

by Muhammad Suzuri Hitam
"... The basic phases in text categorization include preprocessing features, extracting relevant features against the features in a database, and finally categorizing a set of documents into predefined categories. Most of the researches in text categorization are focusing more on the development of algor ..."
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of text categorization. This research proposes an algorithm for preprocessing features with capability of Microsoft.NET framework technology. The actual implementation shows that, this algorithm can extract interested features from the standard corpus of collection and upload into a relational database.
Results 1 - 10 of 91,215