• Proceedings of the KIEE Conference
• /
• 2008.10b
• /
• pp.284-285
• /
• 2008

논문에서는 비전센서로 전방도로영상을 획득하여 차선인식과 정을 거쳐 자율주행에 필요한 도로정보를 추출하고 사고를 방지할 수 있게 경보음을 발생하는 기법을 제시한다. 비전을 통해 입력되는 정보중 직선도로나 곡선도로의 외곽에 해당하는 백색 선만을 인식하는 알고리즘이 필요하다. 이러한 알고리즘을 수행하기 위해서는 많은 계산량이 필요로 하기 때문에 실시간의 자율주행 시스템에의 적용은 제약이 수반된다. 본 논문은 이와 같은 문제를 해결하기 위해 세선화 영역 및 차선이탈경보시스템(LDWS) 알고리즘을 제시한다.

• Proceedings of the KIEE Conference
• /
• 1989.07a
• /
• pp.473-476
• /
• 1989

This paper proposes the recognition of Korean character by using the given pre-segmented area. For higher processing speed, we introduce the techniques for pruning the unused segments. And, new thinning algorithm is used for finding skeleton of each segment.

• 제어로봇시스템학회:학술대회논문집
• /
• 1990.10a
• /
• pp.722-725
• /
• 1990

This paper proposes a new path planning method for obstacle avoidance of mobile robot. In order to achieve easy planning of the path, a simple representation of the empty space is achieved based on thinning algorithm. The proposed Planning technique facilitates the direct use of information obtained by camera. Comparing to the V-graph method, the task of determining the shortest path from the resulting skeleton of empty space is optimized in terms of number of computation steps. The usefulness of the proposed method is ascertained by simulation.

• Proceedings of the Korean Information Science Society Conference
• /
• 2001.04b
• /
• pp.334-336
• /
• 2001

세선화 알고리즘의 간접 기법으로 제시된 자기구성 특징 그래프(Self-Organizing feature Graph : SOG) 기법은 안정된 세선화 결과를 가지는 장점이 있으나 학습 알고리즘에서 전체 노드를 재정돈하는 과정이 내포되어 있다. 본 본문에서는 학습 알고리즘의 재정돈 과정을 대신하는 점증적 정돈기법을 제안하고 이 기법을 세선화 알고리즘에 결합하여 실험하고 분석하였다. 제안된 알고리즘은 기존의 SO를 적용한 결과와 같은 우수한 세선화 결과를 얻으며 학습시간은 O((logM)$^3$)인 복잡도를 가진다.

• Proceedings of the Korean Information Science Society Conference
• /
• 2001.04b
• /
• pp.490-492
• /
• 2001

세선화 알고리즘은 문자 인식에서 인식율을 높이기 위한 전처리과정으로 대상물체에 대하여 1픽셀 두께가 될 때까지 적용시키는 알고리즘으로 그 중요성과 필요성으로 인하여 수많은 논문들이 발표되었다. 본 논문에서는 인터넷 정보검색을 목적으로 하는 회색조(Gray) 영상에 대한 이진화 및 세선화 알고리즘을 제안한다. 제안된 알고리즘은 해당 픽셀과 이웃 화소 간의 픽셀값 차이를 이용하여 일정값을 증감시키는 방법으로, 이미지의 중심으로 픽셀이 응집하게 하는 과정을 통해 이진화 및 세선화를 시켰으며, 병렬 구현이 용이하다. 제안된 알고리즘의 성능평가는 회색조 영상에 대해 기존 알고리즘들을 적용한 결과와 비교, 분석하여 소개하였다.

• Journal of Institute of Control, Robotics and Systems
• /
• v.3 no.2
• /
• pp.179-186
• /
• 1997

In this paper we suggest a development of surface defect inspection algorithms for cold mill strip. The defects which exist in a surface of cold mill strip have a scattering or singular distribution. This paper consists of preprocessing, feature extraction and defect classification. By preprocessing, the binarized defect image is achieved. In this procedure, Top-hit transform, adaptive thresholding, thinning and noise rejection are used. Especially, Top-hit transform using local min/max operation diminishes the effect of bad lighting. In feature extraction, geometric, moment and co-occurrence matrix features are calculated. For the defect classification, multilayer neural network is used. The proposed algorithm showed 15% error rate.

• Proceedings of the KSRS Conference
• /
• v.2
• /
• pp.643-646
• /
• 2006

This paper addresses the approach to extract linear features from satellite imagery using an efficient segmentation method. The extraction of linear features from satellite images has been the main concern of many scientists. There is a need to develop a more capable and cost effective method for the Iranian map revision tasks. The conventional approaches for producing, maintaining, and updating GIS map are time consuming and costly process. Hence, this research is intended to investigate how to obtain linear features from SPOT satellite imagery. This was accomplished using a discontinuity-based segmentation technique that encompasses four stages: low level bottom-up, middle level bottom-up, edge thinning and accuracy assessment. The first step is geometric correction and noise removal using suitable operator. The second step includes choosing the appropriate edge detection method, finding its proper threshold and designing the built-up image. The next step is implementing edge thinning method using mathematical morphology technique. Lastly, the geometric accuracy assessment task for feature extraction as well as an assessment for the built-up result has been carried out. Overall, this approach has been applied successfully for linear feature extraction from SPOT image.

• Journal of ILASS-Korea
• /
• v.6 no.1
• /
• pp.35-43
• /
• 2001

Previous studies on image processing techniques for panicle size measurement usually have focused on a single panicle or weakly overlapped particles. In the present work, the image processing algorithm for particle size measurement has been improved to process heavily-overlapped spherical-particle images. The algorithm consists of two steps; detection of boundaries which separate the images of the overlapped panicles from the background and the panicle identification process. For the first step, Sobel operator (using gray-level gradient) and the thinning process was adopted, and compared with the gray-level thresholding method that has been widely adopted. In the second, Hough transform was used. Hough transform is the detection algorithm of parametric curves such as straight lines or circles which can be described by several parameters. To reduce the measurement error, the process of finding the true center was added. The improved algorithm was tested by processing an image frame which contains heavily overlapped spherical panicles. The results showed that both the performances of detecting the overlapped images and separating the panicle from them were improved.

• Journal of the Institute of Electronics Engineers of Korea TE
• /
• v.37 no.3
• /
• pp.45-52
• /
• 2000

In this study, we propose the image segmentation algorithm for facial region segmentation. The proposed algorithm separates the mean image of low frequency band from the differential image of high frequency band in order to make a boundary using HWT, and then we reduce the isolation pixels, projection pixels, and overlapped boundary pixels from the low frequency band. Also the boundaries are detected and simplified by the proposed boundary detection algorithm, which are cleared on the thinning process of 1 pixel unit. After extracting facial image boundary by using the proposed algorithm, we make the mask and segment facial image through matching original image. In the result of facial region segmentation experiment by using the proposed algorithm, the successive facial segmentation have 95.88% segmentation value.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.1315-1318
• /
• 2004

Based on fuzzy 2-mean classification and template matching method, we propose a new algorithm to detect the edges of an image. In the algorithm, fuzzy 2-mean classification can classify all pixels in the mask into two clusters whatever the mask in the dark or light region; and template matching not only determines the edge's direction, but also thins the detected edge by a set of inference rules and, by the way, reduces the impulse noises.