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- Title
Image Recognition and Classification based on Elastic Model and BOF Algorithm.
- Authors
Mingzhu Liu; Xue Bao; Lu Pang
- Abstract
To solve the problems of mosaic effect and block distortion in the process of image enlargement or reduction, which decrease the accuracy of image recognition and classification, a new fusion algorithm is proposed in this paper. It is a method that integrates an elastic model with the BOF algorithm. Firstly, the distortion phenomenon of static images is studied in depth. Then, the basic principle of the classical BOF algorithm is studied. At the same time, the method and steps of generating feature descriptors using the BOF algorithm are deeply analyzed, and the clustering of feature elements is realized by using the spatial pyramid method. Aiming at the problem of low classification accuracy of scaled images with block distortion, an elastic model method is proposed. It introduces elasticity parameters to scaled image processing and combines the new features obtained by the BOF algorithm to further compensate the block distortion, so as to improve the image recognition accuracy.
- Subjects
IMAGE recognition (Computer vision); IMAGE processing; ALGORITHMS; CLASSIFICATION
- Publication
International Journal of Performability Engineering, 2019, Issue 10, p2794
- ISSN
0973-1318
- Publication type
Article
- DOI
10.23940/ijpe.19.10.p26.27942804