• Title/Summary/Keyword: Character Feature Extraction

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SEL-RefineMask: A Seal Segmentation and Recognition Neural Network with SEL-FPN

  • Dun, Ze-dong;Chen, Jian-yu;Qu, Mei-xia;Jiang, Bin
    • Journal of Information Processing Systems
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    • v.18 no.3
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    • pp.411-427
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    • 2022
  • Digging historical and cultural information from seals in ancient books is of great significance. However, ancient Chinese seal samples are scarce and carving methods are diverse, and traditional digital image processing methods based on greyscale have difficulty achieving superior segmentation and recognition performance. Recently, some deep learning algorithms have been proposed to address this problem; however, current neural networks are difficult to train owing to the lack of datasets. To solve the afore-mentioned problems, we proposed an SEL-RefineMask which combines selector of feature pyramid network (SEL-FPN) with RefineMask to segment and recognize seals. We designed an SEL-FPN to intelligently select a specific layer which represents different scales in the FPN and reduces the number of anchor frames. We performed experiments on some instance segmentation networks as the baseline method, and the top-1 segmentation result of 64.93% is 5.73% higher than that of humans. The top-1 result of the SEL-RefineMask network reached 67.96% which surpassed the baseline results. After segmentation, a vision transformer was used to recognize the segmentation output, and the accuracy reached 91%. Furthermore, a dataset of seals in ancient Chinese books (SACB) for segmentation and small seal font (SSF) for recognition were established which are publicly available on the website.

A Spatial Filtering Neural Network Extracting Feature Information Of Handwritten Character (필기체 문자 인식에서 특징 추출을 위한 공간 필터링 신경회로망)

  • Hong, Keong-Ho;Jeong, Eun-Hwa
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.38 no.1
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    • pp.19-25
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    • 2001
  • A novel approach for the feature extraction of handwritten characters is proposed by using spatial filtering neural networks with 4 layers. The proposed system first removes rough pixels which are easy to occur in handwritten characters. The system then extracts and removes the boundary information which have no influence on characters recognition. Finally, The system extracts feature information and removes the noises from feature information. The spatial filters adapted in the system correspond to the receptive fields of ganglion cells in retina and simple cells in visual cortex. With PE2 Hangul database, we perform experiments extracting features of handwritten characters recognition. It will be shown that the network can extract feature informations from handwritten characters successfully.

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Extraction of the License Plate Region Using HoG and AdaBoost (HoG와 AdaBoost를 이용한 번호판 영역 추출)

  • Lew, Sheen;Yi, Cui-Sheng;Lee, Wan-Joo;Lee, Byeong-Rae;Min, Kyoung-Won;Kang, Hyun-Chul
    • Journal of Digital Contents Society
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    • v.10 no.4
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    • pp.597-604
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    • 2009
  • For the improvement of license plate recognition system, correct extraction of a license plate region as well as character recognition is important. In this paper, with the analysis and classification of the error patterns in the process of plate region extraction, we tried to improve the extraction of the region using HoG(histogram of gradient) features and Adaboost. The results show that the HoG feature is robust to the noise and various types of the plates, and also is very effective to extract the region failed before.

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A Study on Face Component Extraction for Automatic Generation of Personal Avatar (개인아바타 자동 생성을 위한 얼굴 구성요소의 추출에 관한 연구)

  • Choi Jae Young;Hwang Seung Ho;Yang Young Kyu;Whangbo Taeg Ken
    • Journal of Internet Computing and Services
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    • v.6 no.4
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    • pp.93-102
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    • 2005
  • In Recent times, Netizens have frequently use virtual character 'Avatar' schemes in order to present their own identity, there is a strong need for avatars to resemble the user. This paper proposes an extraction technique for facial region and features that are used in generating the avatar automatically. For extraction of facial feature component, the method uses ACM and edge information. Also, in the extraction process of facial region, the proposed method reduces the effect of lights and poor image quality on low resolution pictures. this is achieved by using the variation of facial area size which is employed for external energy of ACM. Our experiments show that the success rate of extracting facial regions is $92{\%}$ and accuracy rate of extracting facial feature components is $83.4{\%}$, our results provide good evidence that the suggested method can extract the facial regions and features accurately, moreover this technique can be used in the process of handling features according to the pattern parts of automatic avatar generation system in the near future.

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Character Element Recognition and Painting Simulation for the Letters to Road Surface (도로 노면 문자 도색을 위한 문자 요소 인식과 도색 실험)

  • Lee, Kyong-Ho;Seong, Jae-Joon
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2016.07a
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    • pp.113-116
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    • 2016
  • 본 논문에서는 사람의 수작업을 통해서 작업을 하고 있는 도로 노면 문자 도색 작업을 자동화하기 위해 문자의 요소 인식과 인식한 결과로 문자 구성 정보를 전달하고, 이 정보를 이용하여 문자를 도색하는 프로그램을 구성하여 도로 노면 문자 도색 모의실험을 수행하였다. 정보처리기기에 프로그램을 구성하여 작업할 문자들을 입력 받아, 이미지 변환과 세선화와 역세선화를 거쳐 만들어진 영상에서 끝점, 2모음점, 3선 이상 모음점, 고립점 등 특징 점들을 추출하고 특징점들을 이용하여 글자를 인식하고, 특징점들을 이용하여 만든 정보를 도로 노면 문자 도색용 장비로 보낸다는 가정 하에 도색 프로그램을 수행 후, 나타난 결과를 피드백 하여 도색 프로그램을 수정하여 도로 노면 문자 도색 작업에 쓸 수 있는 성능의 결과를 구성하였다.

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Image Comparison Using Directional Expansion Operation

  • Yoo, Suk Won
    • International Journal of Advanced Culture Technology
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    • v.6 no.3
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    • pp.173-177
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    • 2018
  • Masks are generated by adding different fonts of learning data characters in pixel unit, and pixel values belonging to each of the masks are divided into 3 groups. Using the directional expansion operators, we expand the text area of the test data character into 4 diagonal directions in order to create the boundary areas to distinguish it from the background area. A mask with a minimum average discordance is selected as the final recognition result by calculating the degree of discordance between the expanded test data and the masks. Image comparison using directional expansion operations more accurately recognizes test data through 4 subdivided recognition processes. It is also possible to expand the ranges of 3 groups of pixel values of masks more evenly such that new fonts can easily be added to the given learning data.

A Study on Vector-based Automatic Caricature Generation (벡터기반의 캐리커처 자동생성에 관한 연구)

  • Park, Yeon-Chool;Oh, Hae-Seok
    • The KIPS Transactions:PartB
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    • v.10B no.6
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    • pp.647-656
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    • 2003
  • This paper proposes the system to generate caricature (character's face) resembling human face using extracted facial features automatically. Since this system is vector-based, the generated character's face has no size limit and constraint. So it is available to transform the shape freely and to apply various facial expressions to 2D face. Moreover, owing to the vector file's advantage, it can be used in mobile environment as small file site.

Development of Character Input System using Facial Muscle Signal and Minimum List Keyboard (안면근 신호를 이용한 최소 자판 문자 입력 시스템의 개발)

  • Kim, Hong-Hyun;Park, Hyun-Seok;Kim, Eung-Soo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.10a
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    • pp.289-292
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    • 2009
  • A person does communication between each other using language. But In the case of disabled person can not communication own idea to use writing and gesture. Therefore, In this paper, we embodied communication system using the facial muscle signals so that disabled person can do communication. Especially, After feature extraction of the EEG included facial muscle, it is converted the facial muscle into control signal, and then select character and communicate using a minimum list keyboard.

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A Study on the Hand-written Number Recognition by HMM(Hidden Markov Model) (HMM을 이용한 수기숫자 인식에 관한 연구)

  • Cho Meen Hwan
    • Journal of the Korea Society of Computer and Information
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    • v.9 no.3
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    • pp.121-125
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    • 2004
  • In the most of recognizing systems of hand-written numbers. extraction of feature shape by using character elements shapes and a method of morphological analysis by using then extraction of feature shapes were usually used. In this paper, however, peculiar chain-code is used, and differential code which gets minimal value by differentiating the chain-code which is generated by the peculiar chain-code is made. We found this differential code is very successful in discriminating hand-written numbers according to the result of applying to most of the hand-written numbers. Testing recognition of hand-written numbers by HMM network. From the results, we can recognize of 96.1 percentage hand-written numbers but can not recognize extremely distorted hand-written numbers.

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Efficiency Evaluation of the Feature Extraction of Roads from Map Image using Morphological Operators* (수리 형태학적 연산자를 이용한 지도 화상에서 도로 정보의 특징 추출에 대한 효율성 평가)

  • 남태희
    • Journal of the Korea Society of Computer and Information
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    • v.4 no.2
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    • pp.19-26
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    • 1999
  • The geographic information system is needed in the image recognition field. This study recommends an efficient method to construct the GIS from the feature extraction of roads through scanning of a normal or hand-made maps. Many algorithms have been presented for such image information recognition. However, such algorithm processes have limitations due to their complexity. To efficiently extract road information from scanning map images. a $3{\times}3$ directional form is applied - structuring element, erosion and dilation, and opening and closing. This method allows for efficient evaluation of the featured road extracts from the map image and from the character sets.

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