• The KIPS Transactions:PartB
• /
• v.11B no.2
• /
• pp.149-158
• /
• 2004

This study proposes a method for segmentation and recognition of traffic signs using shape information and edge image in real image. It first segments traffic sign candidate regions by connected component algorithm from binary images, obtained by utilizing the RGB color ratio of each pixel in the image, and then extracts actual traffic signs based on their symmetries on X- and Y-axes. Histogram equalization is performed for unsegmented candidate regions caused by low contrast in the image. In the recognition stage, it utilizes shape information including projection profiles on X- and Y-axes, moment, and the number of crossings and distance which concentric circular patterns and 8-directional rays from region center intersects with edges of traffic signs. It finally performs recognition by measuring similarity with the templates in the database. It will be shown from several experimental results that the system is robust to environmental factors, such as light and weather condition.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2005.11a
• /
• pp.693-696
• /
• 2005

한의학은 우수한 진단 능력을 보유하고 있음에도 불구하고 임상의의 직관에 머물러 있었던데 비해 서양의학은 다양한 진단 기기 개발로 인해 시장 성숙도 및 선호도에서 발전을 거듭하는 결과를 가져왔다. 본 논문에서는 한방의 직관적 진단법을 시각화, 객관화하기 위해 4진 방법 중 안면 망진 기법을 기기로 구현하기 위한 방법론을 제안하고자 한다. 이를 위해 우선적으로 찰색에 필요한 영역을 자동으로 분할하기 위한 방법을 개발하여 질병 진단에 필요한 진단 데이터를 시각화, 정량화, 계량화하기 위한 작업을 행하고자 한다. 또한 얼굴 안면의 색상 보정을 위해 화이트 밸런스 촬영으로 이미지를 분석하고 얼굴영역을 추출하며, 이목구비와 명당 영역을 추출하여 찰색에 필요한 영역을 분할해 내고자 한다. 끝으로 실험에 의해 제안한 방법의 유용성을 입증하고자 한다.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.1C
• /
• pp.83-91
• /
• 2004

An epipolar rectification is the process of transforming the epipolar geometry of a pair of images into a canonical form. This is accomplished by applying a homography to each image that maps the epipole to a predetermined point. In this process, rectified images transformed by homographies must be satisfied with the epipolar constraint. These homographies are not unique, however, we find out homographies that are suited to system's purpose by means of an additive constraint. Since the rectified image pair be a stereo image pair, we are able to find the disparity efficiently. Therefore, we are able to estimate the three-dimensional information of objects within an image and apply this information to object segmentation. This paper proposes a rectification method for object segmentation and applies the rectification result to the object segmentation. Using color and relative continuity of disparity for the object segmentation, the drawbacks of previous segmentation method, which are that the object is segmented to several region because of having different color information or another object is merged into one because of having similar color information, are complemented. Experimental result shows that the disparity of result image of proposed rectification method have continuity about unique object. Therefore we have confirmed that our rectification method is suitable to the object segmentation.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.9 no.4
• /
• pp.129-138
• /
• 2009

Character graphic design of TV screen, the major visual element, has become greatly important in its roles to help viewers understand visual information better and to enhance the qualities of the program. This research is to figure our a way of changing and improving the attributes of TV captions and graphics such as fonts, size, and caption speed appropriate to bigger and better qualified TV screen. Based on two Delphi surveys of graphics experts along with the theoretical studies, this article analyzes the relevance of visual perception to various visual elements of TV screen, and proposes a better plan in visual effects for various media under OSMU (One Source Multi Use).

• Journal of Korea Society of Industrial Information Systems
• /
• v.22 no.3
• /
• pp.27-38
• /
• 2017

This Paper Presents a Method for Stitching a Large Number of Images Recorded by a Large Number of Individual Users Through a Cellular Phone Camera at a Venue. In Contrast to 360 Camera Solutions that Use Existing Fixed Rigs, these Conditions must Address New Challenges Such as Time Synchronization, Repeated Transformation Matrix Calculations, and Camera Sensor Mismatch Correction. In this Paper, we Solve this Problem by Updating the Transformation Matrix Using Time Synchronization Method Using Audio, Sensor Mismatch Removal by Color Transfer Method, and Global Operation Stabilization Algorithm. Experimental Results Show that the Proposed Algorithm Shows better Performance in Terms of Computation Speed and Subjective Image Quality than that of Screen Stitching.

• Proceedings of the KSRS Conference
• /
• 2008.03a
• /
• pp.20-24
• /
• 2008

차량에 부착된 CCD 카메라를 이용하여 취득된 도로 주변의 영상에 존재하는 사람의 얼굴을 추출하여 제거하는 처리를 할 경우, 사생활 침해의 문제 없이 사용자들에게 원하는 지역의 도로영상의 제공이 가능해진다. 이 실험의 목적은 차량에서 취득된 도로 주변의 칼라 영상에서 사람의 얼굴을 자동으로 추출하는 기술을 개발하는데에 있다. 도로 주변의 CCD영상에서의 얼굴 추출을 위해, HSI(색상, 채도, 명도) 칼라 모델과 YCrCb 칼라 모델을 사용하여 이들 모델에 임계값을 적용하여 피부색을 검출하였으며, 두 개의 모델을 사용한 결과 효과적인 피부색의 검출이 가능함을 확인할 수 있었다. 검출된 피부색 영역을 연결성과 밝기 차이를 이용하여 클러스터링을 실행하고 이렇게 나뉘어진 각각의 구역들에 구역의 면적, 구역내 존재하는 화소의 개수, 구역의 가로와 세로 비율 그리고 타원조건을 적용하여 얼굴 후보 구역을 결정하였다. 그리고 최종적으로 남겨진 구역을 이진화 하고, 이진화 된 영상 중 검은 부분이 5% 이상일 때 이들을 눈, 코, 입 등으로 간주하여 최종적인 얼굴로 결정하였다. 실험 결과 추출되지 않은 얼굴과 잘못 추출된 구역이 발생했으나, 얼굴에 해당하는 임계값등의 조건을 약화시킬 경우 대부분의 얼굴의 추출이 가능할 것으로 여겨지며, 추출된 구역을 흐리게 처리할 경우 오인식된 부분에 대한 사용자의 거부감도 줄일 수 있을 것 으로 예상된다.

• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.2771-2773
• /
• 2001

날씨변화와 차량의 속도차이 등으로 주어지는 외란은 차량번호판을 인식하기 위한 전처리 작업인 영상 추출에 어려움을 준다. 따라서 이러한 외란으로 부터 강인하면서도 효과적으로 번호판을 추출하기 위한 방법으로 Background Marking 방법을 제안한다. 이 방법은 차량의 종류에 따른 번호판 색상 및 인식을 어렵게 하는 여러가지 조건들을 고려함으로써 차량번호판을 보다 효과적으로 추출하는 방법이다. 또한, 히스토그램 정규화를 사용하여 밝기의 차이에 의한 영상의 손상을 보상함으로써 보다 선명한 차량번호판 영상을 습득 할 수 있게 된다. 제안된 방법을 주행 중 또는 주차 중인 차량영상에 적용하여 성능을 검증하였다.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.45 no.3
• /
• pp.160-174
• /
• 2008

In this paper, we propose new coding techniques for photometry data of three-dimensional(3-D) mesh models. We make a good use of geometry and connectivity information to improve coding efficiency of color, normal vector, and texture data. First of all, we determine the coding order of photometry data exploiting connectivity information. Then, we exploit the obtained geometry information of neighboring vortices through the previous process to predict the photometry data. For color coding, the predicted color of the current vertex is computed by a weighted sum of colors for adjacent vortices considering geometrical characteristics between the current vortex and the adjacent vortices at the geometry predictor. For normal vector coding, the normal vector of the current vertex is equal to one of the optimal plane produced by the optimal plane generator with distance equalizer owing to the property of an isosceles triangle. For texture coding, our proposed method removes discontinuity in the texture coordinates and reallocates texture image segments according to the coding order. Simulation results show that the proposed compression schemes provide improved performance over previous works for various 3-D mesh models.

• The KIPS Transactions:PartB
• /
• v.13B no.4 s.107
• /
• pp.353-360
• /
• 2006

This paper presents a robust algorithm for segmenting a vehicle license plate area from a road image. We consider the features of license plates in three aspects : 1) edges due to the characters in the plate, 2) colors in the plate, and 3) geometric properties of the plate. In the preprocessing step, we compute the thresholds based on each feature to decide whether a pixel is inside a plate or not. A statistical approach is applied to the sample images to compute the thresholds. For a given road image, our algorithm binarizes it by using the thresholds. Then, we select three candidate regions to be a plate by searching the binary image with a moving window. The plate area is selected among the candidates with simple heuristics. This algorithm robustly detects the plate against the transformation or the difference of color intensity of the plate in the input image. Moreover, the preprocessing step requires only a small number of sample images for the statistical processing. The experimental results show that the algorithm has 97.8% of successful segmentation of the plate from 228 input images. Our prototype implementation shows average processing time of 0.676 seconds per image for a set of $1280{\times}960$ images, executed on a 3GHz Pentium4 PC with 512M byte memory.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.4C
• /
• pp.388-396
• /
• 2009

This paper proposes a new fire-smoke detection method by using extracted features from camera images and pattern recognition technique. First, moving regions are detected by analyzing the frame difference between two consecutive images and generate candidate smoke regions by applying smoke color model. A smoke region generally has a few characteristics such as similar color, simple texture and upward motion. From these characteristics, we extract brightness, wavelet high frequency and motion vector as features. Also probability density functions of three features are generated using training data. Probabilistic models of smoke region are then applied to observation nodes of our proposed Dynamic Bayesian Networks (DBN) for considering time continuity. The proposed algorithm was successfully applied to various fire-smoke tasks not only forest smokes but also real-world smokes and showed better detection performance than previous method.