Complexity reduced coding of binary pattern units in image classification

The ability to simulate and control complex physical situations in real time is an important element of many engineering and robotics applications, including pattern recognition and image classification. One of the ways to meet specific requirements of a process is a reduction of computational compl...

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Bibliographic Details
Published in:Optics and lasers in engineering Vol. 49; no. 6; pp. 718 - 722
Main Authors: Kurmyshev, E.V., Guillen-Bonilla, J.T.
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.06.2011
Subjects:
Algorithms
Classification
Classification of images
Coding
Complexity
Computational complexity
Fast coordinated clusters representation
Image classification
Pattern recognition
Reduction
Texture
Fast coordinated clusters representation
Pattern recognition
Computational complexity
Classification of images
ISSN:0143-8166, 1873-0302
Online Access:Get full text
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Summary:The ability to simulate and control complex physical situations in real time is an important element of many engineering and robotics applications, including pattern recognition and image classification. One of the ways to meet specific requirements of a process is a reduction of computational complexity of algorithms. In this work we propose a new coding of binary pattern units (BPU) that reduces the time and spatial complexity of algorithms of image classification significantly. We apply this coding to a particular but important case of the coordinated clusters representation (CCR) of images. This algorithm reduces the dimension of the CCR feature space and, as a consequence, the time and space complexity of the CCR based methods of image classification, exponentially. In addition, the new coding preserves all the fundamental properties of the CCR that are successfully used in the recognition, classification and segmentation of texture images. The same approach to the coding of BPUs can be used in the Local Binary Pattern (LBP) method. In order to evaluate the reduction of time and space complexity, we did an experiment on multiclass classification of images using the “traditional” and the new coding of the CCR. This test showed very effective reduction of the computing time and required computer memory with the use of the new coding of BPUs of the CCR, retaining 100% or a little less efficiency of classification at the time. ► We propose a new coding of binary pattern units in image classification. ► This algorithm reduces time and space complexity of CCR and LBP based methods exponentially. ► The coding preserves all fundamental properties of the CCR and LBP classification methods. ► Reduction of computer time and memory is achieved retaining the efficiency of classification.
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ISSN:0143-8166
1873-0302
DOI:10.1016/j.optlaseng.2010.12.014