• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.315-319
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• 2007

This paper presents a algorithm, what is able to recognize 4 different continuous human motion using a single stationary camera as input. For the first step, we acquire images from a camera. To enhance the image, we perform preprocessing which deals with removing noise using median filter, thresholding. And then morphological operations are performed to remove which small blobs and eliminates small holes. At the forth step, blobs are analysed to extracts for foreground region. Then, motions are predicted from these images by using optical flow technique, and the predicted motion data are refined by comparing our cardboard models so as to judge behavior pattern.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.06a
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• pp.33-34
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• 2016

본 논문에서는 HVS(human visual system)의 특성을 고려한 새로운 스케일러블 코딩방법을 제안한다. 제안된 방법은 먼저 영상 내에서 관심영역(saliency map)을 찾고 관심영역을 제외한 부분에 에지 보존 필터를 적용한다. 그 영상은 정해진 양자 파라미터 값으로 인코딩 되어 제안된 코딩 시스템의 베이스 층(base layer)이 된다. 기존 스케일러블 코딩 표준에서의 베이스 층과 다르게 본 논문의 베이스 층은 관심 있는 중요영역(foreground)을 보존하고 또한 배경(background)의 에지 성분도 보존한다. 기본 층이 전송되면 개선층(enhancement layer)은 원 영상과 복원된 베이스 층 영상간의 차분 영상에서 관심영역 순으로 보내진다. 실험은 HEVC 를 바탕으로 수행되었고 스케일러블 코딩 표준인 SHVC 와 관심영역에서 비교를 했을 때 제안된 알고리즘이 더 높은 PSNR 을 가지는 것을 확인하였다. 또한 전체적으로 지각적인 품질(perceptual quality) 또한 향상되었음을 확인하였다.

• Journal of Advanced Navigation Technology
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• v.15 no.3
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• pp.471-477
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• 2011

A wide distribution of CCTV cameras in many public areas can be used not only for video surveillance systems but also for preserving fire occurrence. A proposed approach is based on visual information through a static camera. Video sequences are analyzed to find fire candidates and then spatial analyses procedure for detected fire-like color foreground is carried out. If spatial and temporal variances changes rapidly and close to fire motion, fire candidate is considered as fire.

• Proceedings of the KSPS conference
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• 2000.07a
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• pp.338-349
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• 2000

Pronunciation teaching is once again coming into the foreground of ELT. Japan is, however, lagging far behind many countries in the development of pronunciation curricula and in the actual speech performance of the Japanese learners of English. The reasons for this can be found in the prevalence of communicative methodologies unfavorable for pronunciation teaching, in the lack of trained professionals, and in the large numbers of students in Japanese foreign language classes. This paper offers a way to promote foreign language pronunciation teaching in Japan and other countries by means of employing computer and internet facilities. The paper outlines the major directions of using modem speech technologies in pronunciation classes, like EVF (electronic visual feedback) training at segmental and prosodic levels; automated error detection, testing, grading and fluency assessment. The author discusses the applicability of some specific software packages (CSLU, SUGIspeech, Multispeech, Wavesurfer, etc.) for the needs of pronunciation teaching. Finally, the author talks about the globalization of pronunciation education via internet resources, such as computer corpora and speech and pronunciation training related web pages.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.66-67
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• 2012

본 논문에서는 고정된 카메라로 촬영한 동영상에서 수퍼픽셀(superpixel)을 이용하여 전경 객체 영역을 효과적으로 검출하는 기법을 제안한다. 기존의 픽셀 기반 전경 객체 검출 기법들은 단위 픽셀에 대한 전/배경 판단을 수행하므로 실제 전경 객체 영역에 대한 정확한 검출이 어려운 단점을 지닌다. 수퍼픽셀은 성질이 유사한 픽셀들의 집합을 의미하며 영상의 과도한 분할에 주로 사용되었다. 본 논문에서는 이러한 수퍼픽셀을 이용하여 동영상의 각 프레임을 과도 분할하고, 분할된 각각의 수퍼픽셀을 전경 객체와 배경의 판단 단위로 이용한다. 제안하는 알고리듬을 적용하여 실험한 결과 기존의 픽셀 단위 검출 기법에서 나타났던 오검출을 줄임과 동시에 전경 객체의 형태를 보다 충실하게 검출함을 확인 할 수 있다.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.4
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• pp.231-234
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• 2013

This paper introduces a mixture of background subtraction technique and K-Means clustering algorithm for removing shadows from video sequences. Lighting conditions cause an issue with segmentation. The proposed method can successfully eradicate artifacts associated with lighting changes such as highlight and reflection, and cast shadows of moving object from segmentation. In this paper, K-Means clustering algorithm is applied to the foreground, which is initially fragmented by background subtraction technique. The estimated shadow region is then superimposed on the background to eliminate the effects that cause redundancy in object detection. Simulation results depict that the proposed approach is capable of removing shadows and reflections from moving objects with an accuracy of more than 95% in every cases considered.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.2
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• pp.119-127
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• 2010

In this paper, we propose a new automatic surveillance tracking system that can extract the target from the complex background and foreground noises by using the image-based SAD algorithm and control the servo motor of cameras by using kanatani algorithm. From the experimental results the proposed stereo tracking system is found to track the target adaptively under the circumstance of complex and changing background noises and the possibility of real-time implementation of the proposed system by using the optical system is also suggested.

• Journal of Ubiquitous Convergence Technology
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• v.1 no.1
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• pp.3-8
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• 2007

This paper presents a set of techniques used in a real-time visual surveillance system. The system is implemented on a low-cost embedded DSP platform that is designed to work with stationary video sources. It consists of detection, a tracking and a classification module. The detector uses a statistical method to establish the background model and extract the foreground pixels. These pixels are grouped into blobs which are classified into single person, people in a group and other objects by the dynamic periodicity analysis. The tracking module uses mean shift algorithm to locate the target position. The system aims to control the human density in the surveilled scene and detect what happens abnormally. The major advantage of this system is the real-time capability and it only requires a video stream without other additional sensors. We evaluate the system in the real application, for example monitoring the subway entrance and the building hall, and the results prove the system's superior performance.

• Journal of Information Processing Systems
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• v.10 no.1
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• pp.55-68
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• 2014

Automatic segmentation of foreground text from the background in degraded document images is very much essential for the smooth reading of the document content and recognition tasks by machine. In this paper, we present a novel approach to the binarization of degraded document images. The proposed method uses a new local contrast feature extracted based on the stroke width of text. First, a pre-processing method is carried out for noise removal. Text boundary detection is then performed on the image constructed from the contrast feature. Then local estimation follows to extract text from the background. Finally, a refinement procedure is applied to the binarized image as a post-processing step to improve the quality of the final results. Experiments and comparisons of extracting text from degraded handwriting and machine-printed document image against some well-known binarization algorithms demonstrate the effectiveness of the proposed method.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.520-522
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• 2003

디지털데스크는 일반 책상 표면에 프로젝션 화면을 만들어 가상물체를 사람이 직접 조작할 수 있는 인터페이스를 제공한다. 이러한 인터페이스를 구축하기 위해서는 전경물체 검출이 필수 과정인데, 지금까지는 조명과 배경의 변화로 인한 색상의 변화로 인하여 색상 정보를 사용하지 못하였다. 본 논문에서는 디지털데스크 상에서 색상 정보를 이용하여 전경물체를 검출하는 방법을 제안한다. 디지털데스크의 화면은 프로젝터를 통해 책상 표면에 투사되고, 투사된 화면은 카메라를 통해 영상으로 획득되는데, 이때 많은 왜곡이 존재하게 된다. 우리는 이런 왜곡을 기하 왜곡과 색 휘도의 왜곡 두가지로 정의하여 모델링하였고. 실험 결과에서 제안된 방법의 실효성을 입증하였다.