Fuzzy C-Means Clustering과 Saucola 방법을 통한 문서 영상의 문턱치 처리 기법

• 영문명: Thresholding Technique of Document Image Using Fuzzy C-means Algorithm and Sauvola Method
• 발행기관: 한국IT마케팅학회
• 저자명: 유인준(Jun In Yu) 권영만(Young Man Kwon)
• 간행물 정보: 『한국IT마케팅학회 논문집』한국IT마케팅학회 논문집 1권 1호, 70~71쪽, 전체 2쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2014.11.27

영문 초록

Using the local thresholding, represented by Sauvola method but, Sauvola method of archives, etc. also has been reported that this disadvantage is too light threshold treatment. In this paper, we decided to mitigate the disadvantages of global and local techniques applied to the two-party concepts. First, the threshold values was calculated by applying the method Sauvola. Then, for applying global technique, the new threshold values was determinded using calculated thresholding values by applying the Fuzzy C-Means Clustering. The result is neutralized to an appropriate brightness on the image histogram, and it was confirmed that the threshold value processing.

목차

Abstract

Ⅰ. 서론

Ⅱ. 관련연구

Ⅲ. 실험

Ⅳ. 실험결과

Ⅴ. 결론

참고문헌

키워드

local thresholding global thresholding Sauvola method Fuzzy C-Means Clustering