Text Detection based on Edge Enhanced Contrast Extremal Region and Tensor Voting in Natural Scene Images

• 발행기관: 한국스마트미디어학회
• 저자명: Van Khien Pham Soo-Hyung Kim Hyung-Jeong Yang Guee-Sang Lee
• 간행물 정보: 『스마트미디어저널』Vol6, No.4, 1~9쪽, 전체 9쪽
• 주제분류: 공학 > 컴퓨터학
• 파일형태: PDF
• 발행일자: 2017.12.30

영문 초록

In this paper, a robust text detection method based on edge enhanced contrasting extremal region (CER) is proposed using stroke width transform (SWT) and tensor voting. First, the edge enhanced CER extracts a number of covariant regions, which is a stable connected component from input images. Next, SWT is created by the distance map, which is used to eliminate non-text regions. Then, these candidate text regions are verified based on tensor voting, which uses the input center point in the previous step to compute curve salience values. Finally, the connected component grouping is applied to a cluster closed to characters. The proposed method is evaluated with the ICDAR2003 and ICDAR2013 text detection competition datasets and the experiment results show high accuracy compared to previous methods.

목차

I. INTRODUCTION

II. PROPOSED METHOD

III. EXPERIMENTAL RESULTS

IV. CONCLUSION

키워드

CER MSER SWT Tensor voting Text line information Text detection