Data embedding for camera-based character recognition

Seiichi Uchida; Masakazu Iwamura; Shinichiro Omachi; Koichi Kise

Data embedding for camera-based character recognition

Seiichi Uchida, Masakazu Iwamura, Shinichiro Omachi, Koichi Kise

ENG - Communications Engineering

Research output: Contribution to conference › Paper › peer-review

4 Citations (Scopus)

Abstract

In this paper, the embedment of class information into each character image is investigated for camera-based character recognition as easy and accurate as bar-code reading. Each character image is printed with a horizontal stripe pattern, called a cross ratio pattern, and the class information is represented as a cross ratio derived from the pattern. Since the cross ratio is invariant to projective distortion, the class information is extracted correctly regardless of camera angle. Experimental results showed that the cross ratios are extracted from distorted character images with very high accuracy and thus very effective to attain high character recognition rates.

Original language	English
Pages	60-67
Number of pages	8
Publication status	Published - 2005
Event	1st International Workshop on Camera-Based Document Analysis and Recognition, CBDAR 2005 - Seoul, Korea, Republic of Duration: 2005 Aug 29 → 2005 Aug 29

Other

Other	1st International Workshop on Camera-Based Document Analysis and Recognition, CBDAR 2005
Country	Korea, Republic of
City	Seoul
Period	05/8/29 → 05/8/29

ASJC Scopus subject areas

Computer Vision and Pattern Recognition
Software

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title = "Data embedding for camera-based character recognition",

abstract = "In this paper, the embedment of class information into each character image is investigated for camera-based character recognition as easy and accurate as bar-code reading. Each character image is printed with a horizontal stripe pattern, called a cross ratio pattern, and the class information is represented as a cross ratio derived from the pattern. Since the cross ratio is invariant to projective distortion, the class information is extracted correctly regardless of camera angle. Experimental results showed that the cross ratios are extracted from distorted character images with very high accuracy and thus very effective to attain high character recognition rates.",

author = "Seiichi Uchida and Masakazu Iwamura and Shinichiro Omachi and Koichi Kise",

year = "2005",

language = "English",

pages = "60--67",

note = "1st International Workshop on Camera-Based Document Analysis and Recognition, CBDAR 2005 ; Conference date: 29-08-2005 Through 29-08-2005",

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TY - CONF

T1 - Data embedding for camera-based character recognition

AU - Uchida, Seiichi

AU - Iwamura, Masakazu

AU - Omachi, Shinichiro

AU - Kise, Koichi

PY - 2005

Y1 - 2005

N2 - In this paper, the embedment of class information into each character image is investigated for camera-based character recognition as easy and accurate as bar-code reading. Each character image is printed with a horizontal stripe pattern, called a cross ratio pattern, and the class information is represented as a cross ratio derived from the pattern. Since the cross ratio is invariant to projective distortion, the class information is extracted correctly regardless of camera angle. Experimental results showed that the cross ratios are extracted from distorted character images with very high accuracy and thus very effective to attain high character recognition rates.

AB - In this paper, the embedment of class information into each character image is investigated for camera-based character recognition as easy and accurate as bar-code reading. Each character image is printed with a horizontal stripe pattern, called a cross ratio pattern, and the class information is represented as a cross ratio derived from the pattern. Since the cross ratio is invariant to projective distortion, the class information is extracted correctly regardless of camera angle. Experimental results showed that the cross ratios are extracted from distorted character images with very high accuracy and thus very effective to attain high character recognition rates.

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M3 - Paper

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T2 - 1st International Workshop on Camera-Based Document Analysis and Recognition, CBDAR 2005

Y2 - 29 August 2005 through 29 August 2005

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