• IEIE Transactions on Smart Processing and Computing
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• 제4권1호
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• pp.1-9
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• 2015

Template matching is used for many applications in image processing. One of the most researched topics is object tracking. Normalized Cross Correlation (NCC) is the basic statistical approach to match images. NCC is used for template matching or pattern recognition. A template can be considered from a reference image, and an image from a scene can be considered as a source image. The objective is to establish the correspondence between the reference and source images. The matching gives a measure of the degree of similarity between the image and the template. A problem with NCC is its high computational cost and occasional mismatching. To deal with this problem, this paper presents an algorithm based on the Sum of Squared Difference (SSD) and an adaptive template matching to enhance the quality of the template matching in object tracking. The SSD provides low computational cost, while the adaptive template matching increases the accuracy matching. The experimental results showed that the proposed algorithm is quite efficient for image matching. The effectiveness of this method is demonstrated by several situations in the results section.

• Journal of Computing Science and Engineering
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• 제5권3호
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• pp.161-166
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• 2011

We present a fast algorithm for Korean text extraction and segmentation from subway signboards using smart phone sensors in order to minimize computational time and memory usage. The algorithm can be used as preprocessing steps for optical character recognition (OCR): binarization, text location, and segmentation. An image of a signboard captured by smart phone camera while holding smart phone by an arbitrary angle is rotated by the detected angle, as if the image was taken by holding a smart phone horizontally. Binarization is only performed once on the subset of connected components instead of the whole image area, resulting in a large reduction in computational time. Text location is guided by user's marker-line placed over the region of interest in binarized image via smart phone touch screen. Then, text segmentation utilizes the data of connected components received in the binarization step, and cuts the string into individual images for designated characters. The resulting data could be used as OCR input, hence solving the most difficult part of OCR on text area included in natural scene images. The experimental results showed that the binarization algorithm of our method is 3.5 and 3.7 times faster than Niblack and Sauvola adaptive-thresholding algorithms, respectively. In addition, our method achieved better quality than other methods.

• 대한전자공학회논문지SP
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• 제37권4호
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• pp.56-64
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• 2000

본 논문에서는 패턴인식의 문제에서 배경이 물체에 겹치지 않는 영상일 때 잡음에 대한 안정성, 피크의 크기와 광효율의 조건에 대한 trade-off를 통해 필터를 설계하는 방법에 대해 언급한다. 필터를 설계하기위해 신호대 잡음비, 출력의 최대값대 출력에너지비, 광효율의 세가지 다른 조건을 사용한다. 필터의 성능을 시험하기 위해 여러 형태의 잡음과 필터 계수에 대해 컴퓨터 모의실험을 실시한다. 배경이 물체에 겹치지 않는 영상에 대해 기존의 필터보다 우수한 성능을 얻을 수 있다.

• 한국화재소방학회논문지
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• 제26권2호
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• pp.97-104
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• 2012

본 연구에서는 산불이 발생하면 대형화 위험성이 증대하여 항공기 특히, 헬기의 산불진화 활용성이 점차 증가되고 있는 관점에서, 산불진화 과정 중 헬기에 의한 공중진화기술과 안전성 향상은 효율적인 산불진화의 성공요인으로서 매우 중요하다. 따라서 우리나라 산불전문기관인 산림청 산림항공본부의 조종사들에 대하여 산불현장에서 실제 경험한 내용을 토대로 설문조사를 실시하여 효율적인 공중진화기술 및 안전성 향상 방안을 제시하였다.

• 한국IT서비스학회지
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• 제15권1호
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• pp.245-253
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• 2016

Background in a novel is most important elements with characters and events, and means time, place and situation that characters appeared. Among the background, spatial background can help conveys topic of a novel. So, it may be helpful for choosing a novel that readers want to read. In this paper, we are targeting Korean historical novels. In case of English text, It can be recognize spatial background easily because it use upper and lower case and words used with the spatial information such as Bank, University and City. But, in case Korean text, it is difficult to recognize that spatial background because there is few information about usage of letter. In the previous studies, they use machine learning or dictionaries and rules to recognize about spatial information in text such as news and text messages. In this paper, we build a nation dictionaries that refer to information such as 'Korean history' and 'Google maps.' We Also propose a method for recognizing spatial background based on patterns of postposition in Korean sentences comparing to previous works. We are grasp using of postposition with spatial background because Korean characteristics. And we propose a method based on result of morpheme analyze and frequency in a novel text for raising accuracy about recognizing spatial background. The recognized spatial background can help readers to grasp the atmosphere of a novel and to understand the events and atmosphere through recognition of the spatial background of the scene that characters appeared.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2004년도 정기총회 및 학술대회
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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.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 하계종합학술대회 논문집(4)
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• pp.5-8
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• 2001

We propose a realtime numeric caption recognition algorithm that automatically recognizes the numeric caption generated by computer graphics (CG) and displays the modified caption using the recognized resource only when a valuable numeric caption appears in the aimed specific region of the live sportscast scene produced by other broadcasting stations. We extract the mesh feature from the enhanced binary image as a feature vector after acquiring the sports broadcast scenes using a frame grabber in realtime and then recover the valuable resource from just a numeric image by perceiving the character using the neural network. Finally, the result is verified by the knowledge-based rule set designed for more stable and reliable output and is displayed on a screen as the converted CC caption serving our purpose. At present, we have actually provided the realtime automatic mile-to-kilometer caption conversion system taking up our algorithm f3r the regular Major League Baseball (MLB) program being broadcasted live throughout Korea over our nationwide network. This caption conversion system is able to automatically convert the caption in mile universally used in the United States into that in kilometer in realtime, which is familiar to almost Koreans, and makes us get a favorable criticism from the TV audience.

• 한국멀티미디어학회논문지
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• 제24권12호
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• pp.1641-1652
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• 2021

To analyze the crime scene, the role of digital evidence such as CCTV and black box is very important. Such digital evidence is often damaged due to device defects or intentional deletion. In this case, the deleted video can be restored by well-known techniques like the frame-based recovery method. Especially, the data such as the video can be generally fragmented and saved in the case of the memory used almost fully. If the fragmented video were recovered in units of images, the sequence of the recovered images may not be continuous. In this paper, we proposed a new video restoration method to match the sequence of recovered images. First, the images are recovered through a frame-based recovery technique. Then, after analyzing the time information marked on the images, the time information was extracted and recognized via optical character recognition (OCR). Finally, the recovered images are rearranged based on the time information obtained by OCR. For performance evaluation, we evaluate the recovery rate of our proposed video restoration method. As a result, it was shown that the recovery rate for the fragmented video was recovered from a minimum of about 47% to a maximum of 98%.

• Transactions on Control, Automation and Systems Engineering
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• 제2권1호
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• pp.47-55
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• 2000

In this paper, a vision-based roadway detection algorithm for an automated vehicle control system, based on roadway sign information on roads, is proposed. First, in order to detect roadway signs, the color scene image is enhanced under hue-invariance. Fuzzy logic is employed to simplify the enhanced color image into a binary image and the binary image is morphologically filtered. Then, an effective algorithm of locating signs based on binary rank order transform (BROT) is utilized to extract signs from the image. This algorithm performs better than those previously presented. Finally, the inner shapes of roadway signs with curving roadway direction information are recognized by neural networks. Experimental results show that the new detection algorithm is simple and robust, and performs well on real sign detection. The results also show that the neural networks used can exactly recognize the inner shapes of signs even for very noisy shapes.

• 전자공학회논문지B
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• 제33B권3호
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• pp.79-87
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• 1996

A new method for recognizing and locating partially occluded or overlapped two-dimensional objects regardless of their size, translation, and rotation, is presented. Dominant points approximating occuluding contoures of objects are generated by finding local maxima of smoothed k-cosine function, and then used to guide the contour segment matching procedure. Primitives between the dominant points are produced by projecting the local contours onto the line between the dominant points. Robust classification of primitives. Which is crucial for reliable partial shape matching, is performed using adaptive resonance theory (ART2). The matched primitives having similar scale factors and rotation angles are detected in the hough space to identify the presence of the given model in the object scene. Finally the translation vector is estimated by minimizing the mean squred error of the matched contur segment pairs. This model-based matching algorithm may be used in diveerse factory automation applications since models can be added or changed simply by training ART2 adaptively without modifying the matching algorithm.