• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.73-82
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• 2009

This paper proposes a variance recovery method for character strokes that can be missed in applying the previously proposed color variance approach in text detection of natural scene images. The previous method has a shortcoming of missing the color variance due to the fixed length of horizontal and vertical windows of variance detection when the character strokes are thick or long. Thus, this paper proposes a variance recovery method by using geometric information of bounding boxes of connected components and heuristic knowledge. We have tested the proposed method using various kinds of document-style and natural scene images such as billboards, signboards, etc captured by digital cameras and mobile-phone cameras. And we showed the improved text detection accuracy even in the images of containing large characters.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8C
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• pp.1193-1202
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• 2004

While the management of digital contents is getting more and more important, many researchers have studied about scene change detection algorithms to reduce similar scenes in the video contents and to efficiently summarize video data. The algorithms using histogram and pixel information are found out as being sensitive to light changes and motion. Therefore, visual rhythm gets used in recent work to solve this problem, which shows some characteristics of scenes and requires even less computational power. In this paper, a new scene detection algorithm using visual rhythm by direction is proposed. The proposed algorithm needs less computational power and is able to keep good performance even in the scenes with motion. Experimental results show the performance improvement of about 30% comparing with conventional methods with histogram. They also show that the proposed algorithm is able to keep the same performance even to music video contents with lots of motion.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.06a
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• pp.258-261
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• 2014

The era of realistic broadcast with high fidelity has come after the wide-spread distribution of UHD display and the transmission of UHD experimental broadcast in CATV. However, UHD broadcast now has constraint because it requires much amount of bandwidth and data in broadcasting transmission and production system. Not only HEVC(High Efficiency Video Codec) which has more than two times higher compression rate but also cloud-based editing system would be the key to solve the problems above. Also, fast scene change detection of videos is needed to index and search UHD videos smoothly. In this paper, therefore, a method is proposed to index and search the scene change information of large volume UHD videos compressed with high-efficiency codec. Application usages of fast detection of scene change information in various UHD video environments are considered by using this algorithm.

• Journal of Broadcast Engineering
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• v.2 no.1
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• pp.56-64
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• 1997

An HDTV frame has 4~6 times more pixels than a DTV frame. In order to encode the HDTV image in real time, parallel processing architectures have been widely used in many HDTV codec developments. That is, an HDTV Image is divided into several subbands and each subband is encoded in parallel using some DTV level encoders. In this paper, we adopt an HDTV codec architecture which divides an HDTV frame into 4 subbands and propose a new scene change detection algorithm using local variance. In addition, a new adaptive multichannel rate control scheme which allocate target bits adaptively to each subband of the HDTV image based on the activities of subband images is suggested in this paper. The activities of subband images are calculated at scene change detection part and reused at the adaptive rate control part. The simulation results show that the proposed scene change detection algorithm detects the scene change of HDTV video very accurately. Also the suggested adaptive multichannel rate control scheme shows better performance than the rate control method which allocates target bits equally to each subbands of the HDTV image.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.147-154
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• 2006

Effective and efficient representation of color features of multiple video frames is an important vet challenging task for visual information management systems. This paper Proposes a Video Browsing Service(VBS) that provides both the video content retrieval and the video browsing by the real-time user interface on Web. For the scene segmentation and key frame extraction of video sequence, we proposes an efficient scene change detection method that combine the RGB color histogram with the X2 (Chi Square) histogram. Resulting key frames are linked by both physical and logical indexing. This system involves the video editing and retrieval function of a VCR's. Three elements that are the date, the need and the subject are used for video browsing. A Video Browsing Service is implemented with MySQL, PHP and JMF under Apache Web Server.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.193-201
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• 2006

This paper presents a method that allows for detection of all rapid and gradual scene changes. The method features a combination of the current color histogram and the local $X^{2}-test$. For the purpose of this paper, the $X^{2}-test$ scheme outperforming existing histogram-based algorithms was transformed, and a local $X^{2}-test$ in which weights were applied in accordance with the degree of brightness was used to increase detection efficiency in the segmentation of color values. This Method allows for analysis and segmentation of complex time-varying images in the most general and standardized manner possible Experiments were performed to compare the proposed local $X^{2}-test$ method with the current $X^{2}-test$ method.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.220-228
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• 2022

Image always carry useful information, detecting a text from scene images is imperative. The proposed work's purpose is to recognize scene text image, example boarding image kept on highways. Scene text detection on highways boarding's plays a vital role in road safety measures. At initial stage applying preprocessing techniques to the image is to sharpen and improve the features exist in the image. Likely, morphological operator were applied on images to remove the close gaps exists between objects. Here we proposed a two phase algorithm for extracting and recognizing text from scene images. In phase I text from scenery image is extracted by applying various image preprocessing techniques like blurring, erosion, tophat followed by applying thresholding, morphological gradient and by fixing kernel sizes, then canny edge detector is applied to detect the text contained in the scene images. In phase II text from scenery image recognized using MSER (Maximally Stable Extremal Region) and OCR; Proposed work aimed to detect the text contained in the scenery images from popular dataset repositories SVT, ICDAR 2003, MSRA-TD 500; these images were captured at various illumination and angles. Proposed algorithm produces higher accuracy in minimal execution time compared with state-of-the-art methodologies.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.549-550
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• 2019

In this paper, we propose a method to detect the scene change using deep learning. To extract feature points, we use a deep neural network and express extracted feature points as 128 dimensional vectors using SIFT descriptor. If it is less than 25%, it is determined that the scene is changed.

• The Journal of the Korea Contents Association
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• v.13 no.8
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• pp.1-10
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• 2013

This paper proposes a method to detect vanishing points of an indoor scene using line segment classification. Two-stage vanishing points detection is carried out to detect vanishing point in indoor scene efficiently. In the first stage, the method examines whether the image composition is a one-point perspective projection or a two-point one. If it is a two-point perspective projection, a horizontal line through the detected vanishing point is found for line segment classification. In the second stage, the method detects two vanishing points exactly using line segment classification. The method is evaluated by synthetic images and an image DB. In the synthetic image which some noise is added in, vanishing point detection error is under 16 pixels until the percent of the noise to the image becomes 60%. Vanishing points detection ratio by A.Quattoni and A.Torralba's image DB is over 87%.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.59-66
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• 2011

In this paper, we propose a face detection method based on color constancy and geometrical analysis. With the problem about the various colors of skin under scene illuminant, a color constancy method is applied to input images and geometrical analysis is used to detect face regions. At first, the candidates of face or hair are extracted from the image that a color constancy method is applied to, and are classified by some geometrical criterions. And then, face candidates which have some intersectional regions whose total is over a certain size, with hair candidates are selected as faces. Caltech Face DB was used to compare the performance of our method. Also, performance about scene illuminant was evaluated by images which have some illumination effects. The experiment results show that the proposed face detection method was applicable to various facial images because of high true-positive and low false-negative ration.