• International Journal of Advanced Culture Technology
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• v.6 no.2
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• pp.123-128
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• 2018

Learning data is composed of 100 characters with 10 different fonts, and test data is composed of 10 characters with a new font that is not used for the learning data. In order to consider the variety of learning data with several different fonts, 10 learning masks are constructed by accumulating pixel values of same characters with 10 different fonts. This process eliminates minute difference of characters with different fonts. After finding maximum values of learning masks, test data is expanded by multiplying these maximum values to the test data. The algorithm calculates sum of differences of two corresponding pixel values of the expanded test data and the learning masks. The learning mask with the smallest value among these 10 calculated sums is selected as the result of the recognition process for the test data. The proposed algorithm can recognize various types of fonts, and the learning data can be modified easily by adding a new font. Also, the recognition process is easy to understand, and the algorithm makes satisfactory results for character recognition.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.6
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• pp.455-466
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• 1990

Enalish character recognition with the neural networl algorithm has been performed. Character recognition technition techniques which are processed by software, have the limit of the recognition speed. To overcome this limit, we realize this system to hardware by using the neural network algorithm. We have designed preprocessing chip using the neural nework model, that is single layer perceptorn, in the noise elimination, smoothing, thinning and feature point extraction. These chips are implemented as a CMOS double metal 2um design rule.

• Journal of Korea Multimedia Society
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• v.2 no.3
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• pp.297-307
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• 1999

A character recognition system, where a large amount of character images arrive continuously in real time, must preprocess character images very quickly. Moreover, information loss due to image trans-formations such as geometric normalization and thinning needs to be minimized especially when character images are small and noisy. Therefore, we suggest a prompt and effective feature extraction method without transforming original images. For this, boundary pixels are defined in terms of the degree in classification, and those boundary pixels are considered selectively in extracting features. The proposed method is tested by a handwritten character recognition and a car plate number recognition. The experiments show that the proposed method is effective in recognition compared to conventional methods. And an overall reduction of execution time is achieved by completing all the required processing by a single image scan.

• Journal of the Korea Society of Computer and Information
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• v.22 no.3
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• pp.97-105
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• 2017

This study is the realization study recognizing the Korean gothic printing letter. This study defined the new grapheme by using the connection ingredient and had the graphemes recognized by means of the feature dots of the isolated dot, end dot, 2-line gathering dots, more than 3 lines gathering dots, and classified the characters by means of the arrangement information of the graphemes and the layers that the graphemes form within the characters, and made the character database for the recognition by using them. The layers and the arrangement information of the graphemes consisting in the characters were presumed by using the weight center position information of the graphemes extracted from the characters to recognize and the information of the graphemes obtained by vertically exploring from the weight center of each grapheme, and it recognized the characters by judging and comparing the character groups of the database by means of the information which was secured this way. 350 characters were used for the character recognition test and about 97% recognition result was obtained by recognizing 338 characters.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2004.11a
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• pp.237-240
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• 2004

This paper describes a character retrieval system for TV programs and a set of novel algorithms for detecting and recognizing faces for the system. Our character retrieval system consists of two main components: Face Register and Face Recognizer. The Face Register detects faces in video frames and then guides users to register the detected faces of interest into the database. The Face Recognizer displays the appearance interval of each character on the timeline interface and the list of scenes with the names of characters that appear on each scene. These two components also provide a function to modify incorrect results. which is helpful to provide accurate character retrieval services. In the proposed face detection and recognition algorithms. we reduce the computation time without sacrificing the recognition accuracy by using the DCT/LDA method for face feature extraction. We also develop the character retrieval system in the form of plug-in. By plugging in our system to a cataloguing system. the metadata about the characters in a video can be automatically generated. Through this system, we can easily realize sophisticated on-demand video services which provide the search of scenes of a specific TV star.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.380-382
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• 2021

According to the National Police Agency, 161 out of 38,496 unsolved cases as of 2020. Most of the adult missing persons, the highest of the unsolved causes, are evaluated as simple runaway, which takes a long time to investigate. Even if search through CCTV, it can take a long time and the accuracy can be somewhat low because you have to check the faces of the characters one by one and find the characters only with the characteristics of the statements. This paper utilizes MTCNN to conduct research on character extraction in CCTV. We initiate simultaneous analysis of the features of faces learned with MTCNN and the clothes we are wearing, so that only the overlapping characters are extracted so that they can be identified to the related parties. For aim to learn more diverse feature detection to narrow down the features of missing persons in the future and increase their accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1183-1186
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• 2004

In the steel production line, the molten metal of a furnace is transformed into billet and then moves to the heating furnace of the hot rolling mill. This paper describes about the realtime billet characters recognition system in the steel production line. Normally, the billets are mixed at yard so that their identifications are very difficult and very important processing. The character recognition algorithm used in this paper is base on the subspace method by K-L transformation. With this method, we need no special feature extraction steps, which are usually error prone. So the gray character images are directly used as input vectors of the classifier. To train the classifier, we have extracted eigen vectors of each character used in the billet numbers, which consists of 10 arabia numbers and 26 alphabet aharacters, which are gathered from billet images of the production line. We have developed billet characters recognition system using this algorithm and tested this system in the steel production line during the 8-days. The recognition rate of our system in the field test has turned out to be 94.1% (98.6% if the corrupted characters are excluded). In the results, we confirmed that our recognition system has a good performance in the poor environments and ill-conditioned marking system like as steel production plant.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1275-1277
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• 2003

This paper presents a geological remote sensing information extraction system, the aim of which is to provide practical models and powerful tools to extract geological information from remote sensing images for geological exploration applications. After reviewing and analyzing the existing methods for geological information extraction, we developed more than ten models to enhance and extract geological information, such as alteration information, linear features and special lithological characters. The system is developed based on Erdas Imagine using its programming language. It has been successfully used in the 'reat Investigation of Land and Natural Resources of China' program.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1442-1444
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• 2003

This paper presents a geological remote sensing information extraction system, the aim of which is to provide practical models and powerful tools to extract geological information from remote sensing images for geological exploration applications. After reviewing and analyzing the existing methods for geological information extraction, we developed more than ten models to enhance and extract geological information, such as alteration information, linear features and special lithological characters. The system is developed based on Erdas Imagine using its programming language. It has been successfully used in the ‘Great Investigation of Land and Natural Resources of China’ program.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.315-317
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• 1999

미세한 차이를 고감도 식별하는 카오스 이론의 프랙탈 차원과 스트레인즈 어트랙터를 생성하는 수정된 에농 함수를 이용하여, 한글 2,350자에 대한 시계열 데이터의 혼도도를 분석하기 위해, 각각의 문자 0트랙터를 구성한 후, 프랙탈 차원을 나타내는 Box-counting Dimension 및 Natural Measure, Information Bit, Information Dimension 등을 구하여 문자 특징을 추출하는 새로운 알고리즘을 제시하였다. 실험결과 한글 2,350자에 대하여 99.23%의 분류율을 나타내어 제안된 방법의 유효성을 보였다.