Title: Fast recognition method of text features in dynamic video images

Authors: Guotao Zhao; Jie Ding

Addresses: Hubei Engineering University, Xiaogan, 432000, China ' College of Technology, Hubei Engineering University, Xiaogan, 432000, China

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.

Keywords: dynamic video; image; text feature; fast recognition.

DOI: 10.1504/IJRIS.2020.111781

International Journal of Reasoning-based Intelligent Systems, 2020 Vol.12 No.4, pp.248 - 254

Received: 24 Dec 2019
Accepted: 17 Apr 2020
Published online: 14 Dec 2020 *

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