• KIPS Transactions on Software and Data Engineering
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• v.1 no.2
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• pp.115-126
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• 2012

The artificial captions appearing in videos include information that relates to the videos. In order to obtain the information carried by captions, many methods for caption extraction from videos have been studied. Most traditional methods of detecting caption region have used one frame. However video include not only spatial information but also temporal information. So we propose a method of detection caption region using temporal and spatial information. First, we make improved Text-Appearance-Map and detect continuous candidate regions through matching between candidate-regions. Second, we detect disappearing captions using disappearance test in candidate regions. In case of captions disappear, the caption regions are decided by a merging process which use temporal and spatial information. Final, we decide final caption regions through ANNs using edge direction histograms for verification. Our proposed method was experienced on many kinds of captions with a variety of sizes, shapes, positions and the experiment result was evaluated through Recall and Precision.

• Journal of the Korea Computer Industry Society
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• v.3 no.7
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• pp.901-914
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• 2002

In this paper, We propose an efficient automatic caption detection and location method, caption recognition using FE-MCBP(Feature Extraction based Multichained BackPropagation) neural network for content based retrieval of video. Frames are selected at fixed time interval from video and key frames are selected by gray scale histogram method. for each key frames, segmentation is performed and caption lines are detected using line scan method. lastly each characters are separated. This research improves speed and efficiency by color segmentation using local maximum analysis method before line scanning. Caption detection is a first stage of multimedia database organization and detected captions are used as input of text recognition system. Recognized captions can be searched by content based retrieval method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.8
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• pp.606-610
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• 2004

A noble caption text detection and recognition algorithm using the temporal nature of video is proposed in this paper. A text registration technique is used to locate the temporal and spatial positions of captions in video from the accumulated frame difference information. Experimental results show that the proposed method is effective and robust. Also, a high processing speed is achieved since no time consuming operation is included.

• ETRI Journal
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• v.30 no.5
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• pp.750-752
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• 2008

This paper provides a novel method of detecting key captions containing player information in golf videos. We use the color pattern of captions and its repetition property to determine the key captions. The experimental results show that the proposed method achieves a much higher accuracy than existing methods.

• Journal of Broadcast Engineering
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• v.7 no.2
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• pp.107-113
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• 2002

In this paper, we propose a method and a software system for automatic summarization of baseball game videos. The proposed system pursues fast execution and high accuracy of summarization. To satisfy the requirement, the detection of important events in baseball video is performed through DC-based shot boundary detection algorithm and simple caption recognition method. Furthermore, the proposed system supports a hierarchical description so that users can browse and navigate videos in several levels of summarization. In this paper, we propose a method and a software system for automatic summarization of baseball game videos. The proposed system pursues fast execution and high accuracy of summarization. To satisfy the requirement, the detection of important events in baseball video is performed through DC-based shot boundary detection algorithm and simple caption recognition method. Furthermore, the proposed system supports a hierarchical description so that users can browse and navigate videos in several levels of summarization.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.65-76
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• 2005

A digital video is a very long data that requires large-capacity storage space. As such, prior to watching a long original video, video watchers want to watch a summarized version of the video. In the field of sports, in particular, highlights videos are frequently watched. In short, a highlights video allows a video watcher to determine whether the highlights video is well worth watching. This paper proposes a scheme for creating soccer video highlights using the structural features of captions in terms of time and space. Such structural features are used to extract caption frame intervals and caption keyframes. A highlights video is created through resetting shots for caption keyframes, by means of logical indexing, and through the use of the rule for creating highlights. Finally, highlights videos and video segments can be searched and browsed in a way that allows the video watcher to select his/her desired items from the browser.

• Journal of Broadcast Engineering
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• v.5 no.1
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• pp.113-122
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• 2000

It is sometimes necessary to remove the captions and recover original images from video images already broadcast, When the number of images requiring such recovery is small, manual processing is possible, but as the number grows it would be very difficult to do it manually. Therefore, a method for recovering original image for the caption areas in needed. Traditional research on image restoration has focused on restoring blurred images to sharp images using frequency filtering or video coding for transferring video images. This paper proposes a method for automatically recovering original image using BMA(Block Matching Algorithm). We extract information on caption regions and scene change that is used as a prior-knowledge for recovering original image. From the result of caption information detection, we know the start and end frames of captions in video and the character areas in the caption regions. The direction for the recovery is decided using information on the scene change and caption region(the start and end frame for captions). According to the direction, we recover the original image by performing block matching for character components in extracted caption region. Experimental results show that the case of stationary images with little camera or object motion is well recovered. We see that the case of images with motion in complex background is also recovered.

• Journal of Digital Contents Society
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• v.18 no.7
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• pp.1323-1331
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• 2017

Despite the fact that the copyright has grown into a large-scale business, there are many constant problems especially in image copyright. In this study, we propose an automatic object extraction and classification system for the scanned educational book image by combining document image processing and intelligent information technology like deep learning. First, the proposed technology removes noise component and then performs a visual attention assessment-based region separation. Then we carry out grouping operation based on extracted block areas and categorize each block as a picture or a character area. Finally, the caption area is extracted by searching around the classified picture area. As a result of the performance evaluation, it can be seen an average accuracy of 83% in the extraction of the image and caption area. For only image region detection, up-to 97% of accuracy is verified.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.2
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• pp.590-599
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• 2017

In South Korea, sewage pipeline exploration devices have been developed using high resolution digital cameras of 2 mega-pixels or more. On the other hand, most devices are less than 300 kilo-pixels. Moreover, because 100 kilo-pixels devices are used widely, the environment for image processing is very poor. In this study, very low resolution ($240{\times}320$ = 76,800 pixels) images were adapted when it is difficult to detect cracks. Considering that the images of sewers in South Korea have very low resolution, this study selected low resolution images to be investigated. An automatic crack detection technique was studied using digital image processing technology for low resolution images of sewage pipelines. The authors developed a program to automatically detect cracks as 6 steps based on the MATLAB functions. In this study, the second step covers an algorithm developed to find the optimal threshold value, and the fifth step deals with an algorithm to determine cracks. In step 2, Otsu's threshold for images with a white caption was higher than that for an image without caption. Therefore, the optimal threshold was found by decreasing the Otsu threshold by 0.01 from the beginning. Step 5 presents an algorithm that detects cracks by judging that the length is 10 mm (40 pixels) or more and the width is 1 mm (4 pixels) or more. As a result, the crack detection performance was good despite the very low-resolution images.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2720-2722
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• 2003

이 논문은 연속적인 비디오 영상에서 시간적인 정보를 최대한 이용하는 새로운 캡션검출과 인식알고리즘을 제안하였다. 누적된 차영상 정보로부터 비디오에서 캡션의 시공간적인 위치를 찾아내기 위하여 구문등록 기술을 이용하였다. 그리고 복잡한 배경 영상의 문제를 해결하기 위하여 새로운 다중 프레임 인티그레이션 방법을 이용하였다. 기존 논문과는 달리 빠른 속도의 수행을 위하여 복잡한 계산 과정을 포함하지 않는다. 본 논문에서 제안한 방법은 다양한 뉴스 데이터 영상에서 적용되었고, 그 결과는 아주 정확하고 효과적이었다.