• Journal of Advanced Navigation Technology
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• v.16 no.2
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• pp.394-400
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• 2012

SURF is a robust local invariant feature descriptor and has been used in many applications such as object recognition. Even though this algorithm has similar matching accuracy compared to the SIFT, which is another popular feature extraction algorithm, it has advantage in matching time. However, these descriptors do not consider relative location information of extracted interesting points to guarantee rotation invariance. Also, since they use gray image of original color image, they do not use the color information of images, either. In this paper, we propose a method for improving matching performance of SURF descriptor using the color and relative location information of interest points. The location information is built from the angles between the line connecting the centers of interest points and the orientation line constructed for the center of each interest points. For the color information, color histogram is constructed for the region of each interest point. We show the performance of our scheme through experiments.

• Journal of Digital Contents Society
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• v.10 no.3
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• pp.381-388
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• 2009

This paper proposes a denoising method for the contour edges and crease edges of silhouette obtained from 3D scanned data of stone cultural heritages. It is often the case that the silhouette involves noise in the form of short-length line segments, due to rough surfaces of stone cultural heritages, weathering, and technical difficulties arising in data acquisition. Thus the removal of the short-length line segments from the contour edges and crease edges can result in a clear and accurate silhouette. An efficient computational algorithm is introduced to count the continuity of line segments; edges having not more than 3 line segments are removed. It has been verified that the new method is more effective than threshold-based silhouette extraction methods for stone heritages. Our method is applicable for various other data which are deteriorated by short-length line segments.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.4
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• pp.125-132
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• 2021

As the layers of artificial neural network deepens, and the dimension of data used as an input increases, there is a problem of high arithmetic operation requiring a lot of arithmetic operation at a high speed in the learning and recognition of the neural network (NN). Thus, this study proposes a data dimensionality reduction method to reduce the dimension of the input data in the NN. The proposed Line-segment Feature Analysis (LFA) algorithm applies a gradient-based edge detection algorithm using median filters to analyze the line-segment features of the objects existing in an image. Concerning the extracted edge image, the eigenvalues corresponding to eight kinds of line-segment are calculated, using 3×3 or 5×5-sized detection filters consisting of the coefficient values, including [0, 1, 2, 4, 8, 16, 32, 64, and 128]. Two one-dimensional 256-sized data are produced, accumulating the same response values from the eigenvalue calculated with each detection filter, and the two data elements are added up. Two LFA256 data are merged to produce 512-sized LAF512 data. For the performance evaluation of the proposed LFA algorithm to reduce the data dimension for the recognition of handwritten numbers, as a result of a comparative experiment, using the PCA technique and AlexNet model, LFA256 and LFA512 showed a recognition performance respectively of 98.7% and 99%.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04b
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• pp.565-567
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• 2000

필기 한글 인식에서 원래 패턴의 모양을 유지하는 골격선 추출은 중요하다. 세선화에 의존하는 기존 방법은 작은 잡음에 민감하다는 단점을 안고 있다. 본 논문은 필기 한글 패턴에 적합한 새로운 골격선 추출 방법을 제안한다. 먼저 한글 패턴은 T-접점과 B-접점이라는 두가지 모양 특징을 중심으로 분할할 수 있다는 관찰에 근거하여 유사블록으로 이루어진 부품 집합으로 분할한다. 또한 세 개 이상의 획이 복잡한 형태로 만나는 지점을 결합 부품으로 분할한다. 그런 다음, 각 부품에서 접점의 형태에 따라 결합 부품을 추가 탐지한다. 결합 부품과 인접한 부품들의 연관 관계에 따라 골격선을 구하고, 골격선의 연결성을 보장하기 위해서 선분 연장을 수행한다. 본 논문에서 기존의 방법과의 비교를 위해 다섯 가지 비교 기준을 설정하고, 이를 기반으로 비교 분석하였다. 본 논문에서 제안한 방법이 여러 기준에서 세선화-기반 방법보다 우수함을 보였다.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.651-662
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• 2010

This paper describes a method to identify objects for autonomous navigation of an outdoor mobile robot. To identify objects, the robot recognizes the object from an image taken by moving robot on outdoor environment. As a beginning, this paper presents the candidates for a segment of region to building of artificial object, sky and trees of natural objects. Then we define their characteristics individually. In the process, we segment the regions of the objects included by preprocessing using multiple features. Multiple features are HSI, line segments, context information, hue co-occurrence matrix, principal components and vanishing point. An analysis of building identifies the geometrical properties of building facet such as wall region, windows and entrance. The building as intersection in vertical and horizontal line segment of vanishing point extracts the mesh. The wall region of building detect by merging the mesh of the neighbor parallelograms that have similar colors. The property estimates the number of story and rooms in the same floors by merging skewed parallelograms of the same color. We accomplish the result of image segmentation using multiple features and the geometrical properties analysis of object through experiments.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.610-612
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• 2003

일상 생활에서 자동차의 수가 증가함에 따라 최근 자동차 번호판을 자동으로 인식하는 시스템이 다양한 곳에서 이용되고 있다. 일례로 공항이나 아파트 단지에서 자동으로 문을 개폐해주는 시스템을 도입하고 있다. 기존에 주차권을 통한 개폐기와의 차이점 달려오던 자동차가 일정 속도만 유지하면 자동으로 번호를 인식하는 점이다. 또한 번호판을 통해 정확한 자동차에 대한 정확한 정보를 관리할 수 있다. 이러한 시스템을 위해서 자동차 번호판 영역의 정확한 추출이 필요하다. 본 논문은 자동차 번호판 영역을 RGB영역으로 인식하던 시스템에 수직, 수평 선분을 포함하여 기존에 RGB영역으로 인식하던 시스템의 단점을 보완하고 더 나은 인식시스템 구현하고 실험 하였다.

• Proceedings of the Korea Multimedia Society Conference
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• 2004.05a
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• pp.794-797
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• 2004

본 논문에서는 처리시간을 줄이고, 인식률을 높이기 위해서 이진화된 지문 이미지를 효율적으로 처리하기 위한 자료 구조인 Union and Division을 이용한 이진화와 잡음 제거, 특이점 추출 단계로 이루어진다. Union and Division을 사용하는 경우에서는 융선을 추적 가능하다는 성질을 이용하여서 동일융선 상에 있는 두 개의 특이점을 잇는 선분을 기준점으로 하는 정합 알고리즘을 제안한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.381-384
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• 2004

본 논문에서는 이진화된 지문 이미지를 효율적으로 처리하기 위한 자료 구조인 Union and Division을 이용하여 이진화와 잡음 제거, 그리고 특이점 추출 단계로 이루어진다. Union and Division을 사용하는 경우에, 융선을 추적 가능하다는 성질을 이용하여 동일 융선 상에 있는 두 개의 특이점을 잇는 선분을 기준점으로 하는 정합 알고리즘을 제안한다.

• Journal of KIISE:Software and Applications
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• v.27 no.6
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• pp.583-594
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• 2000

The thinning process which is commonly used in extracting skeletons from handwritten Hangul characters has a problem of distorting the original pattern shapes. This paper proposes a method of skeleton extraction using a shape decomposition algorithm. We decompose the character pattern into a set of near convex parts using a shape decomposition algorithm. From the shape-decomposed pattern, we detect the joint parts and extract the skeletons from the parts incident to the joint parts. Then the skeletons not incident to the joint parts are extracted. Finally, the process of skeleton extension is performed to ensure the connectivity. We setup five criteria for the comparison of quality of skeletons extracted by our method and the thinning based method. The comparison shows the superiority of our method in terms of several criteria.

• Journal of Internet Computing and Services
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• v.9 no.1
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• pp.145-158
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• 2008

The detected arcs by the cone intersection(CI) method exist within a tolerant error from the original curve. But the position of breakpoint by the CI method is sensitive to the tolerant error. The deviation of breakpoint position makes ill effects to the detection of arc center or radius. In this paper a improved CI method for center detection and arc segmentation is proposed. The detected arcs from curves by the proposed method have very stable mean of deviations from the original curves. The experimental results show that the position of breakpoint by the proposed method is closer to real position than the one by other methods.