Automatic detection and recognition of signs from natural scenes

By Xilin Chen, Jie Yang, Jing Zhang, A. Waibel. IEEE Transactions on Image Processing, 2004

338 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Media Technology, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/5295b6770ebbbc27a4651ed44b4b7e184d884f8e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Xiang Bai
2. Cong Yao
3. Luc Van Gool
4. Yu Qiao
5. Dacheng Tao
6. Andrew Zisserman
7. Xiaogang Wang
8. Qixiang Ye

In Media Technology

1. Cong Yao
2. Xiang Bai
3. Qixiang Ye
4. David S. Doermann
5. Xin He
6. Shangbang Long
7. Lukás Neumann
8. Yingli Tian

In Human-Computer Interaction

1. Cong Yao
2. Qixiang Ye
3. David S. Doermann
4. Yingli Tian
5. Chucai Yi
6. Shiguang Shan
7. Lukás Neumann
8. Wen Gao

Citations in the corpus

• A Hybrid Approach to Detect and Localize Texts in Natural Scene Images (2011, methodology): “Chen et al. [4] proposed a hierarchical sign text detection framework by combining multi-scale Laplacian of Gaussian (LOG) edge detection, adaptive search, color analysis and affine normalization.”
• Text String Detection from Natural Scenes by Structure-based Partition and Grouping (2011, methodology): “Some algorithms of scene text normalization are introduced in [4], [18], and [26].”
• Scene Text Detection and Recognition: The Deep Learning Era (2018, methodology): “Various methods have been proposed to tackle these sub-problems , which includes text binarization [71], [93], [139], [167], text line segmentation [155], character segmentation [101], [114], [127], single character recognition [12], [120] and word correction [62], [94], [138], [145], [165].”
• Text Detection and Recognition in Imagery: A Survey (2015, methodology): “However, these approaches often require such assumptions as the existence of a rectangle boundary of text or the availability of camera parameters [13], [26].”
• A Method for Text Localization and Recognition in Real-World Images (2010, background): “Text localization and recognition in images of real-world scenes has received significant attention in the last decade [1–4].”
• Histogram of Gabor Phase Patterns (HGPP): A Novel Object Representation Approach for Face Recognition (2007, methodology): “As a powerful descriptor, the Gabor wavelet is also used in many applications, such as data compression [11], optical character recognition (OCR) [12], texture analysis [13], fingerprint recognition [14], and so on.”