• Journal of Korea Multimedia Society
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• v.24 no.5
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• pp.651-658
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• 2021

In this paper, we propose methods for character recognition and classification for table items through deep learning. First, table areas are detected in a document image through CNN. After that, table areas are separated by separators such as vertical lines. The text in document is recognized through a neural network combined with CNN and RNN. To correct errors in the character recognition, multiple candidates for the recognized result are provided for a sentence which has low recognition accuracy.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.35D no.9
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• pp.62-69
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• 1998

We demonstrated the character display unit using a binary phase hologram array and a liquid crystal-spatial light modulator (LC-SLM). It combines the dynamic property of the LC-SLM with the high-efficiency property of the phase hologram fabricated by photolithography. Experimental results of the proposed unit are presented. The character display unit proposed in this paper has a fundamental and important meaning as new method displaying images by using light, and it will be used in optical information processing and optical communications fields.

• Journal of the Semiconductor & Display Technology
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• v.16 no.3
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• pp.111-115
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• 2017

Terahertz waves are superior to conventional X-ray or Magnetic Resonance Tomography(MRI), and the amount of information that can be transmitted is as large as thousands of times that conventional X-ray or MRI. In addition, Terahertz waves have great performance in analyzing an object which have some layered structure. By using this advantage, we can extract the letters of a page by analyzing information such as absorption amount and reflection amount by irradiating a closed book with pulses of various frequencies within gap of a terahertz wave. However, in the image of each page using the Terahertz wave might be obtained various kinds of noise and the different character occlusion region. So, to extract letters from the terahertz image, we must take the noise and occlusion region away. We have been working to enhancement the image quality in various ways, and keep on studying de-noising processing for enhancement about the image quality and high resolution. Finally, we also keep on studying about OCR(Optical Character Recognition) technology, which based on pattern matching technique, to read letters.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.2
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• pp.433-438
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• 2019

This paper proposes a method of improving deep learning based numbers and characters recognition performance on parts of drawing through image preprocessing. The proposed character recognition system consists of image preprocessing and 7 layer deep learning model. Mathematical morphological filtering is used as preprocessing to remove the lines and shapes which causes false recognition of numbers and characters on parts drawing. Further.. Further, the used deep learning model is a 7 layer deep learning model instead of VGG-16 model. As a result of the proposed OCR method, the recognition rate of characters is 92.57% and the precision is 92.82%.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.2
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• pp.11-19
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• 2023

In this paper, we propose the methods of invoice document structure recognition and of making a spreadsheet electronic document. The texts and block location information of word blocks are recognized by an optical character recognition engine through deep learning. The word blocks on the same row and same column are found through their coordinates. The document area is divided through arrangement information of the word blocks. The character recognition result is inputted in the spreadsheet based on the document structure. In simulation result, the item placement through the proposed method shows an average accuracy of 92.30%.

• Journal of Information Processing Systems
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• v.12 no.1
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• pp.100-108
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• 2016

In this paper, we propose a method to achieve improved number plate detection for mobile devices by applying a multiple convolutional neural network (CNN) approach. First, we processed supervised CNN-verified car detection and then we applied the detected car regions to the next supervised CNN-verifier for number plate detection. In the final step, the detected number plate regions were verified through optical character recognition by another CNN-verifier. Since mobile devices are limited in computation power, we are proposing a fast method to recognize number plates. We expect for it to be used in the field of intelligent transportation systems.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1772-1773
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• 2011

현대기술의 발전에 따라 계측기술 또한 다양하고 복잡하게 변모하였으며, 정밀측정기기의 교정 업무에서는 복잡하고 정확한, 반복적이며 계속적인 데이터 취득을 요구한다. 또한 여러 장비를 사용할 경우, 장시간 소요되는 데이터 취득과 정확한 계측기 사용법 및 고도의 관련기술을 필요로 한다. 그러므로 컴퓨터를 이용 한 계측장비 제어로 측정에 필요한 시간을 최대한 단축하고, 개인오차를 제거할 수 있는 동일한 결과와 쉽게 데이터를 취득할 수 있도록 측정자동화가 필요하다.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.109.2-109
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• 2001

In the PCB assembly lines, as components become more complex and smaller, the conventional inspection method using traditional ICT and function test show their limitations in application. The automatic optical inspection(AOI) gradually becomes the alternative in the PCB assembly line. In Particular, the PCB inspection machines need more reliable and flexible object recognition algorithms for high inspection accuracy. The conventional AOI machines use the algorithmic approaches such as template matching, Fourier analysis, edge analysis, geometric feature recognition or optical character recognition (OCR), which mostly require much of teaching time and expertise of human operators. To solve this problem, in this paper, a statistical learning based part recognition method is proposed. The performance of the ...

• Journal of the Optical Society of Korea
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• v.12 no.1
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• pp.52-56
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• 2008

An all-optical read only memory utilizing cross gain modulation in semiconductor optical amplifiers (SOAs) has been demonstrated for the first time to our knowledge. In our demonstration, an all-optical 2-to-4 line decoder constructed with SOAs has been employed for the construction of this all-optical read only memory. Storing four characters in an American standard code for information interchange (ASCII) format has been successfully carried out. Each character consisting of seven binary bits could be read out at a rate of 10 Giga characters per second.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.544-546
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• 2001

이 논문은 OCR(Optical Character Reader)로 인식된 한글 문서에서의 오인식 경향을 분석하고, 이를 이용한 한글 단어 검색 방법을 제안한다. OCR로 인식된 많은 야의 한글 문서를 기반으로 자모별 인식 빈도수를 계산하고 이를 바탕으로 초성, 중성, 중성별 인식 혼동 행렬(confusion matrix)을 구성하였다. 또한 인식 정보를 적절히 이용하기 Bayes 정리를 이용하였다. 질의어에 대한 오인식 단어의 검색 방법을 제시하고 혼동 행렬과 이 검색 방법을 바탕으로 OCR 기반 단어 검색 시스템을 구축하였다.