• Journal of Korea Entertainment Industry Association
• /
• v.5 no.1
• /
• pp.127-133
• /
• 2011

Characters in natural image are an important information with various context. Previous work of character region detection algorithms is not detect of character region in case of image complexity and the surrounding lighting, similar background to character, so this paper propose an method of character region detection in natural image using edge and connected component by morphological reconstructions. Firstly, we detect edge using Canny-edge detector and connected component with local min/max value by morphological reconstructed-operation in gray-scale image, and labeling each of detected connected component elements. lastly, detected candidate of text regions was merged for generation for one candidate text region, Final text region detected by checking the similarity and adjacency of neighbor of text candidate individual character. As the results of experiments, proposed algorithm improved the correctness of character regions detection using edge and connected components.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.11
• /
• pp.188-194
• /
• 2013

In this paper, we proposed a new method for pulmonary vessels image segmentation and refinement from pulmonary image. Proposed method consist of following five steps. First, threshold estimation is performed by polynomial regression analysis of histogram variation rate of the pulmonary image. Second, segmentation of pulmonary vessels object is performed by density-based segmentation method based on estimated threshold in first step. Third, 2D connected component labeling method is applied to segmented pulmonary vessels. The seed point of both side diaphragms is determined by eccentricity and size of component. Fourth step is diaphragm extraction by 3D region growing method at the determined seed point. Finally, noise cancelation of pulmonary vessels image is performed by 3D connected component labeling method. The experimental result is showed accurately pulmonary vessels image segmentation, the diaphragm extraction and the noise cancelation of the pulmonary vessels image.

• Proceedings of the Korean Information Science Society Conference
• /
• 2002.04b
• /
• pp.646-648
• /
• 2002

본 논문에서는 차량번호판의 용도구분 문자를 자소 단위로 분리하는 효율적인 방법을 제안하고, 신경망을 이용하여 자소를 인식하는 방법을 소개한다. 용도구분 문자(가, 거, 나, 너‥‥)는 실제 번호판의 훼손, 카메라의 성능, 기타 여러 가지 조건에 의해서 번호판 영상에 많은 잡영이 포함된다. 따라서 차량번호판 한글문자를 자소분리하는 것은 어려운 작업이다. 제안하는 이진 영상처리 기법(morphological operation, connected component labeling 등) 으로 분리된 자소가 인식시스템으로의 입력벡터로 입력되었을 때 높은 인식률을 보이는 것을 실험을 통하여 확인하였다

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2012.07a
• /
• pp.286-289
• /
• 2012

본 논문은 3차원 깊이 정보를 이용하여 감시카메라에서 움직이는 사람을 검출하고 추적하는 방법을 제안한다. 제안하는 방법은 GMM(Gaussian mixture model)을 이용하여 배경과 움직이는 사람을 분리한 후, 분리된 영역을 CCL(connected-component labeling)을 통하여 각각 블랍(blob) 단위로 나누고 그 블랍을 추적한다. 그 중 블랍 단위로 나누는 데 있어 두 블랍이 합쳐진 경우, 3차원 깊이 정보를 이용하여 두 블랍을 분리하는 방법을 제안한다. 실험을 통하여 제안하는 방법의 결과를 보인다.

• Proceedings of the Korea Multimedia Society Conference
• /
• 2003.11a
• /
• pp.245-248
• /
• 2003

볼륨데이터에서 관심대상의 특징을 추출하기 위해서 3D레이블링을 3차원 세포영상의 분석에 적합한 레이블링 방법인 SIL(slice Information base labeling)을 제안하였다. SIL은 각 슬라이스 정보를 이용하여 레이블링을 수행하므로 영상의 특징에 안는 레이블링으로의 확장이 유용하고 메모리 효율이 높다. 몇 개의 실험 영상으로 다른 방법과 비교한 결과 성능면에서도 우수 결과를 얻었다. 또한 레이블링을 통해서 얻어진 피쳐값으로 세포 영상을 분석하였으며, 콘포컬 현미경 영상을 이용하였을때 실험영상에서 결과를 추출하는데 걸린 시간은 SIL방법이 기존 방법보다 2배 가량 빨랐다. 다양한 3차원 에이블링 방법 중 적용되는 영상에 따라 각기 다른 결과를 얻었지만,3차원 세포영상의 분석에는 SIL 방법이 우수하다는 결론을 얻었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2006.05a
• /
• pp.796-799
• /
• 2006

This paper presents a new method for automatic detection of skew in a document image using mathematical morphology. To speed up processing, we use reduced image but it still requires long time to estimate the skew angle so the proposed method works with region of interest, not with whole image. Character strings are connected by using morphological closing operation and a component labeling is used to select region of interest. The method considers the lowermost pixels of characters in candidate regions in the binary image of original document image. Experimental results shows that the proposed method is extremely fast and robust as well as independent of script forms.

• The KIPS Transactions:PartB
• /
• v.14B no.1 s.111
• /
• pp.1-4
• /
• 2007

In this paper, we propose an efficient scheme for automatically detecting highlight scenes in soccer videos. Highlights are defined as shooting scenes and goal scenes. Through the analysis of soccer videos, we notice that most of highlight scenes are shown around the goal post area. It is also noticed that the TV camera zooms in a setter player or spectators after the highlight stones. Detection of highlight scenes for soccer videos consists of three steps. The first step is the extraction of the playing field using a statistical threshold. The second step is the detection of goal posts. In the final step, we detect a zooming of a soccer player or spectators by using connected component labeling of non-playing field. In order to evaluate the performance of our method, the precision and the recall are computed. Experimental results have shown the effectiveness of the proposed method, with 95.2% precision and 85.4% recall.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.3
• /
• pp.847-852
• /
• 2010

Text in natural images has a various and important feature of image. Therefore, to detect text and extraction of text, recognizing it is a studied as an important research area. Lately, many applications of various fields is being developed based on mobile phone camera technology. Detecting edge component form gray-scale image and detect an boundary of text regions by local standard deviation and get an connected components using Euclidean distance of RGB color space. Labeling the detected edges and connected component and get bounding boxes each regions. Candidate of text achieved with heuristic rule of text. Detected candidate text regions was merged for generation for one candidate text region, then text region detected with verifying candidate text region using ectilarity characterization of adjacency and ectilarity between candidate text regions. Experctental results, We improved text region detection rate using completentary of edge and color connected component.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.21 no.6
• /
• pp.705-711
• /
• 2011

This paper proposes an effective algorithm of license plate recognition for industrial applications. By applying Canny edge detection on a vehicle image, it is possible to find a connected rectangular, which is a strong candidate for license plate. The color information of license plate separates plates into white and green. Then, OTSU binary image processing and foreground neighbor pixel propagation algorithm CLNF will be applied to each license plates to reduce noise except numbers and letters. Finally, through labeling, numbers and letters will be extracted from the license plate. Letter and number regions, separated from the plate, pass through mesh method and thinning process for extracting feature vectors by X-Y projection method. The extracted feature vectors are compared with the pre-learned weighting values by backpropagation neural network to execute final recognition process. The experiment results show that the proposed license plate recognition algorithm works effectively.

• Journal of Sensor Science and Technology
• /
• v.12 no.3
• /
• pp.128-138
• /
• 2003

In this paper, we proposed the algorithm for locating destination address block (DAB) from automatic system to classify packages. For locating DAB, because the size of obtained images is are very large, we select the region of interesting (ROI) to reduce time carrying into algorithm. After selecting the ROI, proposed algorithm is carried out within the ROI. We extract the outline of the handwriting part of the DAB and the rest components within the obtained ROI using thresholding. We carry out labeling to extract each connected component for extracted outline and the rest components. We extract the outline of the handwriting part of the DAB using the geometrical characteristic of the outline of the handwriting part of the DAB among many connected components. The last, we extract the locating DAB using the outline of the handwriting part of the DAB.