• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.2
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• pp.1-9
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• 2008

In this paper, to extract object regions in stereo image, we propose an enhanced algorithm that extracts objects combining both of brightness information and disparity information. The approach that extracts objects using both has been studied by Ping and Chaohui. In their algorithm, the segmentation for an input image is carried out using the brightness, and integration of segmented regions in consideration of disparity information within the previously segmented regions. In the regions where the brightness values between object regions and background regions are similar, however, the segmented regions probably include both of object regions and background regions. It may cause incorrect object extraction in the merging process executed in the unit of the segmented region. To solve this problem, in proposed method, we adopt the merging process which is performed in pixel unit. In addition, we perform the bi-directional stereo matching process to enhance reliability of the disparity information and supplement the disparity information resulted from a single directional matching process. Further searching for disparity is decided by edge information of the input image. The proposed method gives good performance in the object extraction since we find the disparity information that is not extracted in the traditional methods. Finally, we evaluate our method by experiments for the pictures acquired from a real stereoscopic camera.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.73-76
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• 2002

비디오 시청을 원하는 사용자들은 비디오의 전반적인 개요를 짧은 시간에 시청하여 보고싶은 비디오를 쉽게 선택하기를 바란다. 본 논문에서는 전환 검출 방법과 샷 클러스터링을 이용한 비디오 개요 추출 방법을 제시한다. 장면전환 검출 방법은 컬러 히스토그램과 χ2 히스토그램을 합성한 방법을 이용하여 추출하도록 한다. 클러스터링은 히스토그램의 차이값을 측정과 샷 병합 알고리즘을 통해 수행하도록 한다.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.472-474
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• 2001

본 논문은 wavelet 기반의 watershed를 이용한 효율적인 영상 분할을 기법을 제안한다. 영상 분할을 위해 입력 영상을 wavelet transform을 사용하여 low-resolution 영상을 생성한 후 watershed 알고리즘을 이용해 분할하고, 이를 Inverse wavelet transform함으로써 원 영상으로 복원한다. 복원된 영상을 의미 있는 영역들로 분할하기 위해 wavelet 특징값의 유사성을 두 인접한 영역에 비교하여 병합한다. 실험 결과 제안한 방법은 영상의 잡음에 대한 강인함과 영상의 과분할 문제를 해결할 수 있다.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.299-300
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• 2006

In this paper, we propose a segmentation algorithm which combines the ideas from local watershed transforms and the region merging algorithm based hierarchical queue. Only the process of watershed and region merging algorithm can be restricted area. A fast region merging approach is proposed to extract the video object from the regions of watershed segmentation. Results show the effectiveness and convenience of the approach.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.583-587
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• 2002

비디오를 시청하기 위하여 원하는 비디오를 선택하고자 할 때 사용자들은 비디오의 전반적인 내용을 알 수 있는 방법이 많지 않다. 따라서 비디오 시청을 원하는 사용자들에게 비디오의 전반적인 개요를 보여주어 선택 할 수 있는 방법이 요구된다. 본 논문에서는 전환 검출 방법과 샷 클러스터링을 이용한 비디오 개요 추출 방법을 제시한다. 장면전환 검출 방법은 컬러 히스토그램과 $\times$2 히스토그램을 합성한 방법을 이용하여 추출하도록 한다. 클러스터링은 히스토그램의 차이값을 측정과 샷 병합 알고리즘을 통해 수행하도록 한다.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.37-39
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• 2004

본 논문은 점증적으로 갱신되는 온톨로지에 기반한 스키마 매칭 알고리즘을 제안한다. 스키마 매칭에 사용되는 온톨로지는 전운가에 의하여 작성된 정적인 것으로 모든 어휘관계를 포괄하기는 힘들다. 제안된 방법은 이전의 매칭 결과와 사용자 피드백에 따라 점증적으로 온틀로지를 갱신하여 매칭의 성능을 향상시킨다. 특히, 제안된 온톨로지는 분할, 병합 관계를 기술하고 있어 단순한 애칭관계분만 아니라 복합매칭관계 추출을 가능케 한다. 성능평가를 위한 실험결과 점증적 온틀로지의 적용이 매칭 성능을 매우 향상시킴을 알 수 있었다.

• Journal of KIISE:Information Networking
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• v.36 no.1
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• pp.24-33
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• 2009

In patch-and-stitch localization algorithms, a flip error refers to the kind of error in which a patch is stitched to the map as being wrongly reflected. In this paper, we present an anchor-free localization algorithm which tries to detect and prevent flip errors. The flip error prevention is achieved by two filtering mechanisms: the flip-ambiguity test and the flip-conflict detection. We evaluate the performances of proposed techniques though simulations and show that they achieve significant performance improvements.

• Communications for Statistical Applications and Methods
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• v.18 no.1
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• pp.89-102
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• 2011

The discretization process that converts continuous attributes into discrete ones is a preprocessing step in data mining such as classification. Some classification algorithms can handle only discrete attributes. The purpose of discretization is to obtain discretized data without losing the information for the original data and to obtain a high predictive accuracy when discretized data are used in classification. Many discretization algorithms have been developed. This paper presents the results of our comparative study on recently proposed representative discretization algorithms from the view point of splitting versus merging and supervised versus unsupervised. We implemented R codes for discretization algorithms and made them available for public users.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.1
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• pp.47-54
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• 2008

In this paper, we propose an auto-detection algorithm of basal cell carcinoma(BCC) from the protophorphyrin IX(PpIX) fluorescence image induced by appling the methyl 5-aminolaevulinate(MAL) ointment-induced protophorphyrin IX(PpIX) to the skin tumour area and then shining the wood lamp on the area. The proposed algorithm first generates 3 mask areas-tumor area, suspected tumor area and tumor free area and then applies local watershed algorithm to the turner and the suspected tumor areas to make small watershed regions that include similar luminance value pixels. Next, small watershed regions are merged by hierarchical queue based fast region merging that uses the difference between the average luminance values of adjacent watershed regions as a region merging criterion and finally BCC regions are detected. 50 tissue samples are acquired from the tumour regions of 10 patients with BCC that are extracted by using the proposed algorithm and are performed pathological examination by expert dermatologist. Experiment result shows the rate of tumor detection from BCC lesion using presurgical in vivo of MAL-indeuced PpIX fluorescence has high sensitivity 94.1% and relatively high specificity 82.6%.

• Journal of the Korea Society of Computer and Information
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• v.16 no.7
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• pp.105-115
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• 2011

In Vision-based Intelligent Transportation System(ITS) the segmentation of road region is a very basic functionality. Accordingly, in this paper, we propose a region segmentation method using adaptive pattern extraction technique to segment road regions and sky regions from original images. The proposed method consists of three steps; firstly we perform the initial segmentation using Mean Shift algorithm, the second step is the candidate region selection based on a static-pattern matching technique and the third is the region growing step based on a dynamic-pattern matching technique. The proposed method is able to get more reliable results than the classic region segmentation methods which are based on existing split and merge strategy. The reason for the better results is because we use adaptive patterns extracted from neighboring regions of the current segmented regions to measure the region homogeneity. To evaluate advantages of the proposed method, we compared our method with the classical pattern matching method using static-patterns. In the experiments, the proposed method was proved that the better performance of 8.12% was achieved when we used adaptive patterns instead of static-patterns. We expect that the proposed method can segment road and sky areas in the various road condition in stable, and take an important role in the vision-based ITS applications.