Fast recognition method of text features in dynamic video images Online publication date: Mon, 14-Dec-2020
by Guotao Zhao; Jie Ding
International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 12, No. 4, 2020
Abstract: In order to improve the text recognition ability of dynamic video image, a fast text feature recognition method based on block area contour detection is proposed. The fuzzy video feature analysis method is used to collect the text features of the dynamic video image, reorganise the frame structure, and extract the edge features of the text features of the image. The collected text features are fused into multi-dimensional information, and the edge contour feature information of dynamic video image is matched by block matching method. In this paper, a packet fusion model of Chinese text feature in dynamic video image is established, and the corner detection of text feature is carried out by surf algorithm to realise the fast recognition of Chinese text feature in dynamic video image. Simulation results show that the maximum SNR of the image text feature recognition output is 44.8 dB, and the recognition accuracy is high.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Reasoning-based Intelligent Systems (IJRIS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com