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Study on OCR Enhancement of Homomorphic Filtering with Adaptive Gamma Value
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적응형 감마값을 이용한 동형 필터링의 OCR 향상에 관한 연구

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Type
Academic journal
Author
Heeyeon Jo (Yonsei University) Jeongwoo Lee (Yonsei University) Hongrae Lee (Yonsei University)
Journal
The Korean Society Of Computer And Information Journal of the Korea Society of Computer and Information Vol.29 No.2(Wn.239) KCI Accredited Journals
Published
2024.2
Pages
101 - 108 (8page)

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Study on OCR Enhancement of Homomorphic Filtering with Adaptive Gamma Value
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AI-OCR (Artificial Intelligence Optical Character Recognition) combines OCR technology with Artificial Intelligence to overcome limitations that required human intervention. To enhance the performance of AI-OCR, training on diverse data sets is essential. However, the recognition rate declines when image colors have similar brightness levels. To solve this issue, this study employs Homomorphic filtering as a preprocessing step to clearly differentiate color levels, thereby increasing text recognition rates. While Homomorphic filtering is ideal for text extraction because of its ability to adjust the high and low frequency components of an image separately using a gamma value, it has the downside of requiring manual adjustments to the gamma value. This research proposes a range for gamma threshold values based on tests involving image contrast, brightness, and entropy. Experimental results using the proposed range of gamma values in Homomorphic filtering suggest a high likelihood for effective AI-OCR performance.
#AI-OCR #Optical Character Recognition(OCR) #Preprocessing #Homomorphic Filtering #Adaptive Threshold Range #광학 문자 인식 (OCR) #전처리 #호모모픽 필터링 #적응적 임계 범위

Contents

Abstract
요약
Ⅰ. Introduction
Ⅱ. Related works
Ⅲ. The Proposed Scheme
Ⅳ. Experiments
Ⅴ. Conclusion and Future Work
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