• The Journal of the Korea Contents Association
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• v.14 no.3
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• pp.11-21
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• 2014

Multi-scale image segmentation is important in many applications such as image stylization and medical diagnosis. This paper proposes a novel segmentation algorithm based on MSER(maximally stable extremal region) which captures multi-scale structure and is stable and efficient. The algorithm collects MSERs and then partitions the image plane by redrawing MSERs in specific order. To denoise and smooth the region boundaries, hierarchical morphological operations are developed. To illustrate effectiveness of the algorithm's multi-scale structure, effects of various types of LOD control are shown for image stylization. The proposed technique achieves this without time-consuming multi-level Gaussian smoothing. The comparisons of segmentation quality and timing efficiency with mean shift-based Edison system are presented.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.6
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• pp.194-203
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• 2008

Though conventional video surveillance systems such as CCTV depended on operators, recently developed intelligent surveillance systems no longer needed operators. However, these new intelligent surveillance systems have their own problems such as Occlusion, changing scale of target object, and affine. This paper handled information damage caused by changing the scale of the target object among other objects. Due to the change of the scale, the inaccurate information of target can be obtained when we update the background information. To handle this problem, we introduce a solution for information damage caused by problem of changing scale of target object located among other objects. Specifically, we suggest multi-stage sampling particle filter based advanced MSER for object tracking system. Through this method, the problem caused by changing scale of target can be avoided.

• Annual Conference of KIPS
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• 2013.11a
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• pp.1709-1712
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• 2013

교통 신호등은 운전자 혹은 보행자들의 뚜렷한 시인성 확보를 위해 가능한 주위 배경과 구분되는 색상, 모양, 질감 등으로 구성하여 설치되어 있는 특징을 가지고 있다. 결국 기존 교통 신호등 검출 연구들에서는 대부분 교통 신호등의 색상과 모양을 기반으로 한 검출 연구가 주류를 이루고 있는 것이 사실이다. 하지만, 외부 날씨, 복잡한 시내, 다른 물체와의 겹침 등의 문제로 인해 색상 및 모양 기반의 교통 신호등, motion blur, 검출 오류가 증가 되고 있다. 따라서 본 연구에서는 입력 영상에서 색상정보를 배제하고 motion blur나 밝기 변화에 덜 민감하고 먼 거리에서도 뛰어난 시인성을 가진 spot light 검출을 통해 입력 영상에서 가장 밝은 교통표지판 후보 영역들을 검출한다. 그리고 교통 신호등의 특징인 가능한 원형을 유지하고 있으며 원형 외부 색상과 내부 색상이 현저하게 두드러지는 영역을 maximally stable extremal regions (MSER) 알고리즘을 사용하여 입력 영상에서 후보 영역을 선택한다. 마지막으로, 검출된 영역들에서 교통 신호등 영역을 검출하기 위해 템플릿 매칭 방법을 적용한다. 제안한 방법을 도로 상에서 실험한 결과, 평균 94% 이상의 검출율을 제시하였고, 특히 야간 시간대에 검출율이 비교적 높게 제시되었다.

• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.61-68
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• 2018

In this paper, we propose a method of character detection by analyzing image enhancement and character type to detect characters in natural images that can be acquired in everyday life. The proposed method emphasizes the boundaries of the object part using the unsharp mask in order to improve the detection rate of the area to be recognized as a character in a natural image. By using the boundary of the enhanced object, the character candidate region of the image is detected using Maximal Stable Extermal Regions (MSER). In order to detect the region to be judged as a real character in the detected character candidate region, the shape of each region is analyzed and the non-character region other than the region having the character characteristic is removed to increase the detection rate of the actual character region. In order to compare the objective test of this paper, we compare the detection rate and the accuracy of the character region with the existing methods. Experimental results show that the proposed method improves the detection rate and accuracy of the character region over the existing character detection method.