IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

A Hierarchical Target Recognition Method Based on Image Processing

A Hierarchical Target Recognition Method Based on Image Processing
View Sample PDF
Author(s): QingE Wu (Zhengzhou University of Light Industry, China)and Weidong Yang (Fudan University, China)
Copyright: 2018
Pages: 17
Source title: Computer Vision: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-5204-8.ch019

Purchase

View A Hierarchical Target Recognition Method Based on Image Processing on the publisher's website for pricing and purchasing information.

Abstract

In order to provide an accurate and rapid target recognition method for some military affairs, public security, finance and other departments, this paper studies firstly a variety of fuzzy signal, analyzes the uncertainties classification and their influence, eliminates fuzziness processing, presents some methods and algorithms for fuzzy signal processing, and compares with other methods on image processing. Moreover, this paper uses the wavelet packet analysis to carry out feature extraction of target for the first time, extracts the coefficient feature and energy feature of wavelet transformation, gives the matching and recognition methods, compares with the existing target recognition methods by experiment, and presents the hierarchical recognition method. In target feature extraction process, the more detailed and rich texture feature of target can be obtained by wavelet packet to image decomposition to compare with the wavelet decomposition. In the process of matching and recognition, the hierarchical recognition method is presented to improve the recognition speed and accuracy. The wavelet packet transformation is used to carry out the image decomposition. Through experiment results, the proposed recognition method has the high precision, fast speed, and its correct recognition rate is improved by an average 6.13% than that of existing recognition methods. These researches development in this paper can provide an important theoretical reference and practical significance to improve the real-time and accuracy on fuzzy target recognition.

Related Content

Aswathy Ravikumar, Harini Sriraman. © 2023. 18 pages.
Ezhilarasie R., Aishwarya N., Subramani V., Umamakeswari A.. © 2023. 10 pages.
Sangeetha J.. © 2023. 13 pages.
Manivannan Doraipandian, Sriram J., Yathishan D., Palanivel S.. © 2023. 14 pages.
T. Kavitha, Malini S., Senbagavalli G.. © 2023. 36 pages.
Uma K. V., Aakash V., Deisy C.. © 2023. 23 pages.
Alageswaran Ramaiah, Arun K. S., Yathishan D., Sriram J., Palanivel S.. © 2023. 17 pages.
Body Bottom