• Journal of the Korean Institute of Telematics and Electronics
• /
• v.27 no.3
• /
• pp.116-123
• /
• 1990

Most algorithms utilized the horizontal epipolar lines for solving the correspondence problem in 3-D computer vision. However, the requirement is very difficult to be satisfied in real situations. In this paper, we propose a binocular-stereo matching algorithm, based on line matching method, which does not require the horizontal epipolar lines of the extreme pixels of a given line segment and two circles whose radius is equal to the maximum disparity. And we use the features including the direction of line segments, edge strength and cross-correlation for line matching. The experimental results show that the proposed algorithm can be a useful tool for solving the correspondence problem in 3-D computer vision.

• Korean Journal of Cognitive Science
• /
• v.3 no.2
• /
• pp.271-289
• /
• 1992

In this paper,a cursive on-line Hangul recognition system which permits cursive writing between graphemes is presented.In general,the recognition of cursive Hangul writing has a difficulty of graheme segmentation and a complexity in matching procedure due to the increasing number of character candidates.To manage efficiently these problems,we propose a double segmentation method.Based on this segmentation,a recognition algorithm based on the line segment matching is proposed.Through the experimental result,it is show that the proposed recognition method is suitable for the cursive Hangul writings.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.5
• /
• pp.483-488
• /
• 2008

An active omni-directional raging system using an omni-directional vision with structured light has many advantages compared to the conventional ranging systems: robustness against external illumination noise because of the laser structured light and computational efficiency because of one shot image containing $360^{\circ}$ environment information from the omni-directional vision. The omni-directional range data represents a local distance map at a certain position in the workspace. In this paper, we propose a matching algorithm for the local distance map with the given global map database, thereby to localize a mobile robot in the global workspace. Since the global map database consists of line segments representing edges of environment object in general, the matching algorithm is based on relative position and orientation of line segments in the local map and the global map. The effectiveness of the proposed omni-directional ranging system and the matching are verified through experiments.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.33B no.3
• /
• pp.79-87
• /
• 1996

A new method for recognizing and locating partially occluded or overlapped two-dimensional objects regardless of their size, translation, and rotation, is presented. Dominant points approximating occuluding contoures of objects are generated by finding local maxima of smoothed k-cosine function, and then used to guide the contour segment matching procedure. Primitives between the dominant points are produced by projecting the local contours onto the line between the dominant points. Robust classification of primitives. Which is crucial for reliable partial shape matching, is performed using adaptive resonance theory (ART2). The matched primitives having similar scale factors and rotation angles are detected in the hough space to identify the presence of the given model in the object scene. Finally the translation vector is estimated by minimizing the mean squred error of the matched contur segment pairs. This model-based matching algorithm may be used in diveerse factory automation applications since models can be added or changed simply by training ART2 adaptively without modifying the matching algorithm.

• Proceedings of the KSRS Conference
• /
• 2007.10a
• /
• pp.234-237
• /
• 2007

Road networks are important geospatial databases for various GIS (Geographic Information System) applications. Road digital maps may contain geometric spatial errors due to human and scanning errors, but manually updating roads information is time consuming. In this paper, we developed a new road features updating methodology using from multispectral high-resolution satellite image and pre-existing vector map. The approach is based on initial seed point generation using line segment matching and a modified double snake algorithm. Firstly, we conducted line segment matching between the road vector data and the edges of image obtained by Canny operator. Then, the translated road data was used to initialize the seed points of the double snake model in order to refine the updating of road features. The double snake algorithm is composed of two open snake models which are evolving jointly to keep a parallel between them. In the proposed algorithm, a new energy term was added which behaved as a constraint. It forced the snake nodes not to be out of potential road pixels in multispectral image. The experiment was accomplished using a QuickBird pan-sharpened multispectral image and 1:5,000 digital road maps of Daejeon. We showed the feasibility of the approach by presenting results in this urban area.

• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.59-64
• /
• 2002

This paper presents a method for line segment extraction for 3-d building reconstruction. Building roofs are described as a set of planar polygonal patches, each of which is extracted by watershed-based image segmentation, line segment matching and coplanar grouping. Coplanar grouping and polygonal patch formation are performed per region by selecting 3-d line segments that are matched using epipolar geometry and flight information. The algorithm has been applied to high resolution aerial images and the results show accurate 3-d building reconstruction.

• Transactions on Electrical and Electronic Materials
• /
• v.17 no.6
• /
• pp.363-368
• /
• 2016

Rectangular shape detection plays an important role in many image recognition systems. However, it requires continued research for its improved performance. In this study, we propose a strong rectangular shape detection algorithm, which combines the canny edge and line detection algorithms based on the perpendicularity and parallelism of a rectangle. First, we use the canny edge detection algorithm in order to obtain an image edge map. We then find the edge of the contour by using the connected component and find each edge contour from the edge map by using a DP (douglas-peucker) algorithm, and convert the contour into a polyline segment by using a DP algorithm. Each of the segments is compared with each other to calculate parallelism, whether or not the segment intersects the perpendicularity intersecting corner necessary to detect the rectangular shape. Using the perpendicularity and the parallelism, the four best line segments are selected and whether a determined the rectangular shape about the combination. According to the result of the experiment, the proposed rectangular shape detection algorithm strongly showed the size, location, direction, and color of the various objects. In addition, the proposed algorithm is applied to the license plate detecting and it wants to show the strength of the results.

• Journal of Institute of Control, Robotics and Systems
• /
• v.20 no.11
• /
• pp.1153-1163
• /
• 2014

An efficient 3D SLAM (Simultaneous Localization and Map Building) method is developed for urban building environments using a tilted 2D LRF (Laser Range Finder), in which a 3D map is composed of perpendicular/horizontal planar polygons. While the mobile robot is moving, from the LRF scan distance data in each scan period, line segments on the scan plane are successively extracted. We propose an "expected line segment" concept for matching: to add each of these scan line segments to the most suitable line segment group for each perpendicular/horizontal planar polygon in the 3D map. After performing 2D localization to determine the pose of the mobile robot, we construct updated perpendicular/horizontal infinite planes and then determine their boundaries to obtain the perpendicular/horizontal planar polygons which constitute our 3D map. Finally, the proposed SLAM algorithm is validated via extensive simulations and experiments.

• Korean Journal of Remote Sensing
• /
• v.11 no.3
• /
• pp.61-70
• /
• 1995

In this paper, the algorithm to extract the height of flat-rooftop structures in stereo aerial image is suggested with an assumption that location, orientation, focal length, and field of view of a camera are known. It can be adapted to stereo aerial or satellite images. For performing feature-based stereo matching, the line segments suitable to describe the shape of general buildings are chosen as the feature. This paper is composed of three categories;the first step is to extract edges of structures with the polygon extraction algorithm which utilizes the edge following method, the second step is to perform the line segment matching with the camera information, and the last step is to calculate the location of each matched line and to estimate heights. The stereo images used in experiments are not real but synthetic ones. The experiment shows good results.

• The KIPS Transactions:PartA
• /
• v.17A no.4
• /
• pp.189-196
• /
• 2010

This paper presents an improved marker detection algorithm using hybrid features such as corner, line segment, region, and adaptive threshold values, etc. In usual augmented reality environments, there are often marker occlusion and poor illumination. However, existing ARToolkit fails to recognize the marker in these situations, especially, partial concealment of marker by user, large change of illumination and dim circumstances. In order to solve these problems, the adaptive threshold technique is adopted to extract a marker region and a corner extraction method based on line segments is presented against marker occlusions. In addition, a compensating method, corresponding the marker size and center between registered and extracted one, is proposed to increase the template matching efficiency, because the inside marker size of warped images is slightly distorted due to the movement of corner and warping. Therefore, experimental results showed that the proposed algorithm can robustly detect the marker in severe illumination change and occlusion environment and use similar markers because the matching efficiency was increased almost 30%.