• Title/Summary/Keyword: video character recognition

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Study on News Video Character Extraction and Recognition (뉴스 비디오 자막 추출 및 인식 기법에 관한 연구)

  • 김종열;김성섭;문영식
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.40 no.1
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    • pp.10-19
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    • 2003
  • Caption information in news videos can be useful for video indexing and retrieval since it usually suggests or implies the contents of the video very well. In this paper, a new algorithm for extracting and recognizing characters from news video is proposed, without a priori knowledge such as font type, color, size of character. In the process of text region extraction, in order to improve the recognition rate for videos with complex background at low resolution, continuous frames with identical text regions are automatically detected to compose an average frame. The image of the averaged frame is projected to horizontal and vertical direction, and we apply region filling to remove backgrounds to produce the character. Then, K-means color clustering is applied to remove remaining backgrounds to produce the final text image. In the process of character recognition, simple features such as white run and zero-one transition from the center, are extracted from unknown characters. These feature are compared with the pre-composed character feature set to recognize the characters. Experimental results tested on various news videos show that the proposed method is superior in terms of caption extraction ability and character recognition rate.

Character Recognition and Search for Media Editing (미디어 편집을 위한 인물 식별 및 검색 기법)

  • Park, Yong-Suk;Kim, Hyun-Sik
    • Journal of Broadcast Engineering
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    • v.27 no.4
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    • pp.519-526
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    • 2022
  • Identifying and searching for characters appearing in scenes during multimedia video editing is an arduous and time-consuming process. Applying artificial intelligence to labor-intensive media editing tasks can greatly reduce media production time, improving the creative process efficiency. In this paper, a method is proposed which combines existing artificial intelligence based techniques to automate character recognition and search tasks for video editing. Object detection, face detection, and pose estimation are used for character localization and face recognition and color space analysis are used to extract unique representation information.

Development of a Video Caption Recognition System for Sport Event Broadcasting (스포츠 중계를 위한 자막 인식 시스템 개발)

  • Oh, Ju-Hyun
    • 한국HCI학회:학술대회논문집
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    • 2009.02a
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    • pp.94-98
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    • 2009
  • A video caption recognition system has been developed for broadcasting sport events such as major league baseball. The purpose of the system is to translate the information expressed in English units such as miles per hour (MPH) to the international system of units (SI) such as km/h. The system detects the ball speed displayed in the video and recognizes the numerals. The ball speed is then converted to km/h and displayed by the following character generator (CG) system. Although neural-network based methods are widely used for character and numeral recognition, we use template matching to avoid the training process required before the broadcasting. With the proposed template matching method, the operator can cope with the situation when the caption’s appearance changed without any notification. Templates are configured by the operator with a captured screenshot of the first pitch with ball speed. Templates are updated with following correct recognition results. The accuracy of the recognition module is over 97%, which is still not enough for live broadcasting. When the recognition confidence is low, the system asks the operator for the correct recognition result. The operator chooses the right one using hot keys.

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Multi-Style License Plate Recognition System using K-Nearest Neighbors

  • Park, Soungsill;Yoon, Hyoseok;Park, Seho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.5
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    • pp.2509-2528
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    • 2019
  • There are various styles of license plates for different countries and use cases that require style-specific methods. In this paper, we propose and illustrate a multi-style license plate recognition system. The proposed system performs a series of processes for license plate candidates detection, structure classification, character segmentation and character recognition, respectively. Specifically, we introduce a license plate structure classification process to identify its style that precedes character segmentation and recognition processes. We use a K-Nearest Neighbors algorithm with pre-training steps to recognize numbers and characters on multi-style license plates. To show feasibility of our multi-style license plate recognition system, we evaluate our system for multi-style license plates covering single line, double line, different backgrounds and character colors on Korean and the U.S. license plates. For the evaluation of Korean license plate recognition, we used a 50 minutes long input video that contains 138 vehicles of 6 different license plate styles, where each frame of the video is processed through a series of license plate recognition processes. From two experiments results, we show that various LP styles can be recognized under 50 ms processing time and with over 99% accuracy, and can be extended through additional learning and training steps.

Video character recognition improvement by support vector machines and regularized discriminant analysis (서포트벡터머신과 정칙화판별함수를 이용한 비디오 문자인식의 분류 성능 개선)

  • Lim, Su-Yeol;Baek, Jang-Sun;Kim, Min-Soo
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.4
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    • pp.689-697
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    • 2010
  • In this study, we propose a new procedure for improving the character recognition of text area extracted from video images. The recognition of strings extracted from video, which are mixed with Hangul, English, numbers and special characters, etc., is more difficult than general character recognition because of various fonts and size, graphic forms of letters tilted image, disconnection, miscellaneous videos, tangency, characters of low definition, etc. We improved the recognition rate by taking commonly used letters and leaving out the barely used ones instead of recognizing all of the letters, and then using SVM and RDA character recognition methods. Our numerical results indicate that combining SVM and RDA performs better than other methods.

A Hangeul Recognition Method Using Directional Edges in Open Captions

  • Jun, Seung-Chul;Kang, Myeong-Gyu;Park, Sung-Han
    • Proceedings of the IEEK Conference
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    • 2002.07b
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    • pp.1157-1160
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    • 2002
  • This paper proposes an efficient method to recognize Hangeul in video open captions. The open captions in news video can play an important role in the video indexing. The strokes of Korean character have a very strong horizontal and vertical directionality and some strokes appear repeatedly in each character. Based on this characteristics, in this paper, we propose an efficient algorithm to extract the character regions in open caption and recognize the characters based on these characteristics of Korean character. The simulation results demonstrate the efficiency of our algorithm in terms of computation time and recognition accuracy.

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CARA: Character Appearance Retrieval and Analysis for TV Programs

  • Jung Byunghee;Park Sungchoon;Kim Kyeongsoo
    • 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.

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Study on Performance Evaluation of Automatic license plate recognition program using Emgu CV (Emgu CV를 이용한 자동차 번호판 자동 인식 프로그램의 성능 평가에 관한 연구)

  • Kim, Nam-Woo;Hur, Chang-Wu
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.6
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    • pp.1209-1214
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    • 2016
  • LPR(License plate recognition) is a kind of the most popular surveillance technology based on accompanied by a video and video within the optical character recognition. LPR need a many process. One is a localization of car license plates, license plate of size, space, contrast, normalized to adjust the brightness, another is character division for recognize the character optical character recognition to win the individual characters, character recognition, the other is phrase analysis of the shape, size, position by year, the procedure for the analysis by comparing the database of license plate having a difference by region. In this paper, describing the results of performance of license plate recognition S/W, which was implemented using EmguCV, find the location, using the tesseract OCR, which are well known to an optical character recognition engine of open source, the characters of the license plate image capturing angle of the plate, image size, brightness.

Major Character Extraction using Character-Net (Character-Net을 이용한 주요배역 추출)

  • Park, Seung-Bo;Kim, Yoo-Won;Jo, Geun-Sik
    • Journal of Internet Computing and Services
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    • v.11 no.1
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    • pp.85-102
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    • 2010
  • In this paper, we propose a novel method of analyzing video and representing the relationship among characters based on their contexts in the video sequences, namely Character-Net. As a huge amount of video contents is generated even in a single day, the searching and summarizing technologies of the contents have also been issued. Thereby, a number of researches have been proposed related to extracting semantic information of video or scenes. Generally stories of video, such as TV serial or commercial movies, are made progress with characters. Accordingly, the relationship between the characters and their contexts should be identified to summarize video. To deal with these issues, we propose Character-Net supporting the extraction of major characters in video. We first identify characters appeared in a group of video shots and subsequently extract the speaker and listeners in the shots. Finally, the characters are represented by a form of a network with graphs presenting the relationship among them. We present empirical experiments to demonstrate Character-Net and evaluate performance of extracting major characters.

Effects of Caption-Utilized English Classes on Primary School Students' Character Recognition and Vocabulary Ability (자막을 활용한 영어수업이 초등학생의 문자인지 능력과 어휘력에 미치는 효과)

  • So, Suk;Lee, Je-Young;Hwang, Chee-Bok
    • The Journal of the Korea Contents Association
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    • v.18 no.7
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    • pp.423-431
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    • 2018
  • The purpose of the present study was to investigate the effect of caption-embedded video on character recognition and vocabulary ability of the primary school students, The subjects of this study were the students in two elementary schools in G city, Jeonbuk province. They were divided into two groups including a control group which used utilization video materials without captions, and a experimental group which used utilization video materials with captions. Each group was tested over the course of two months (10 classes). And then a statistical analysis was conducted to find out the effects of captions on character recognition and vocabulary ability through independent samples t-test and paired samples t-test. There were no significant differences in a comparison between the groups, but significant differences were found within the groups. Pedagogical implications based on the research findings and suggestions for further research were also discussed.