• The KIPS Transactions:PartB
• /
• v.18B no.4
• /
• pp.221-230
• /
• 2011

Digital comic images are one of popular contents on the Internet. Usually, they are scanned from comic books by digital scanners. Without post-processing, they may have different sizes, skews and margins other than contents at the boundary. To normalize the size of their contents without the skews and margins is an important step in comic image analysis and application such as content-based comic image retrieval system. In this paper, we propose a method to detect a box frame in comic images by extracting of line segments using the gradient Radon transform. The box frame in comic images is the maximum rectangle which consists of contents without margins. We use the detected box frame to normalize the size of comic images and to make them no skew. In addition, the proposed method is implemented by OpenCL to speed up the detection of the line segments. Experimental results show that our proposed method effectively detects the box frame in comic images.

• Journal of Broadcast Engineering
• /
• v.13 no.2
• /
• pp.236-244
• /
• 2008

We propose a new building detection and description algorithm for Lidar data and photogrammetric imagery using color segmentation, line segments matching, perceptual grouping. Our algorithm consists of two steps. In the first step, from the initial building regions extracted from Lidar data and the color segmentation results from the photogrammetric imagery, we extract coarse building boundaries based on the Lidar results with split and merge technique from aerial imagery. In the secondstep, we extract precise building boundaries based on coarse building boundaries and edges from aerial imagery using line segments matching and perceptual grouping. The contribution of this algorithm is that color information in photogrammetric imagery is used to complement collapsed building boundaries obtained by Lidar. Moreover, linearity of the edges and construction of closed roof form are used to reflect the characteristic of man-made object. Experimental results on multisensor data demonstrate that the proposed algorithm produces more accurate and reliable results than Lidar sensor.

• Journal of IKEEE
• /
• v.27 no.1
• /
• pp.1-11
• /
• 2023

Path driving tests are necessary for the development of self-driving cars or robots. These tests are being conducted in simulation as well as real environments. In particular, for development using reinforcement learning and deep learning, development through simulators is also being carried out when data of various environments are needed. To this end, it is necessary to utilize not only manually designed paths but also various randomly and automatically designed paths. This test site design can be used for actual construction and manufacturing. In this paper, we introduce a method for randomly generating a driving test path consisting of a combination of arcs and segments. This consists of a method of determining whether there is a collision by obtaining the distance between an arc and a line segment, and an algorithm that deletes part of the path and recreates an appropriate path if it is impossible to continue the path.

• 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%.

• Journal of the Institute of Convergence Signal Processing
• /
• v.13 no.4
• /
• pp.180-186
• /
• 2012

In this paper, a method of edge detection from low contrast and noisy images which contain hexagonal shape is proposed. This method is based on the combination of laplacian gaussian filter and an idea of filters which are dependent on the shape. First, an algorithm which has six masks as its extractors to detect the hexagonal edges especially in the comers is used. Here, two tricom filters are used to detect the tricom joints of hexagons and other four masks are used to enhance the line segments of hexagonal edges. As a natural image, a corneal endothelial cell image which usually has a regular hexagonal shape is selected. The edge detection of hexagonal shapes in this corneal endothelial cell is important for clinical diagnosis. Next, The proposal algorithm and other conventional methods are applied to noisy hexagonal images to evaluate each efficiency. As a result, this proposal algorithm shows a robustness against noises and better detection ability in the aspects of the signal to noise ratio, the edge coineidence ratio and the detection accuracy factor as compared with other conventional methods.

• Bulletin of the Korean Space Science Society
• /
• 2008.10a
• /
• pp.28.1-28.1
• /
• 2008

Detection of spectral bio-signatures from extra terrestrial planets has received an increasing attention from the astronomy and space science communities in recent years. In an attempt to better-understand disk averaged spectra of the only know terrestrial planet i.e. Earth, we are constructing a scale-able 3D earth model with surface reflectance and scattering properties. The USGS coastal line data were used to form coastal line segments and they were then stitched to generate continuous coastal lines to represent major continents and large islands. As the first stage of model verification, wavelength dependent ocean and land reflectance data and scattering characteristics were defined over the land and sea surfaces respectively. We then performed ray tracing based imaging and radiometric transfer simulations using a hypothetical optical payload receiving the reflected and scattered sun lights from the earth. The model concept, computational details, the simulation results are discussed as well as the future development plan.

• Journal of the Korea Society for Simulation
• /
• v.16 no.1
• /
• pp.31-37
• /
• 2007

The importance of NPC's role in computer games is increasing. An NPC must perform its tasks by perceiving obstacles and other characters and by moving through them. It has been proposed to plan a natural-looking path against fixed obstacles by using a generalized visibility graph. In this paper we develop the execution module for an NPC to move efficiently along the path planned on the generalized visibility graph. The planned path consists of line segments and arc segments, so we define steering behaviors such as linear behaviors, circular behaviors, and an arriving behavior for NPC's movements to be realistic and utilize them during execution. The execution module also includes the collision detection capability to be able to detect dynamic obstacles and uses a decision tree to react differently according to the detected obstacles. The execution module is tested through the simulation based on the example scenario in which an NPC interferes the other moving NPC.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2007.04a
• /
• pp.153-156
• /
• 2007

There have been many studies on extracting building boundaries from LiDAR(Light Detection And Ranging) data. In such studies, points are first segmented, then are further processed to get straight boundary lines that better approximate the real boundaries. In most research in this area, processes like generalization or regularization assume that buildings have only right angles, i.e. all the line segments of the building boundaries are either parallel or perpendicular. However, this assumption is not valid for many buildings. We present a new approach consisting of three steps that is applicable to more complex building boundaries. The three steps consist of boundary tracing, generalization, and regularization. Each step contains algorithms that range from slight modifications of conventional algorithms to entirely new concepts. Four typical building shapes were selected to test the performance of out new approach and the results were compared with digital maps. The results show that the proposed approach has good potential for extracting building boundaries of various shapes.

• Journal of Korea Multimedia Society
• /
• v.15 no.6
• /
• pp.737-747
• /
• 2012

Recently, in order to support automatic meter reading for conventional metering devices, an image processing-based approach of recognizing the number meter data in the captured meter images has attracted many researchers' interests. Numerical character segmentation is a very critical process for successful recognition. In this paper, we propose an efficient numeric character segmentation method which can segment numeric characters well for any metering device types under diverse illumination environments. The proposed method consists of two consecutive stages; detection of number area containing all numbers as a tight ROI(Region of Interest) and segmentation of numerical characters in the ROI. Detection of tight ROI is achieved in two steps: extraction of rough ROI by utilizing horizontal line segments after illumination enhancement preprocessing, and making the rough ROI more tight through clipping utilizing vertical and horizontal projection about binarized ROI. Numerical character segmentation in the detected ROI is stably achieved in two processes of 'vertical segmentation of each number region' and 'number segmentation in the each vertical segmented number region'. Through the experiments about a homegrown meter image database containing various meter type images of low contrast, low intensity, shadow, and saturation, it is shown that the proposed numeric character segmentation method performs effectively well for any metering device types under diverse illumination environments.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.31 no.4
• /
• pp.331-339
• /
• 2013

LiDAR has been one of the widely used and important technologies for 3D modeling of ground surface and objects because of its ability to provide dense and accurate range measurement. The objective of this research is to develop a method for automatic detection and modeling of railroad power lines using high density LiDAR data and RANSAC algorithms. For detecting railroad power lines, multi-echoes properties of laser data and shape knowledge of railroad power lines were employed. Cuboid analysis for detecting seed line segments, tracking lines, connecting and labeling are the main processes. For modeling railroad power lines, iterative RANSAC and least square adjustment were carried out to estimate the lines parameters. The validation of the result is very challenging due to the difficulties in determining the actual references on the ground surface. Standard deviations of 8cm and 5cm for x-y and z coordinates, respectively are satisfactory outcomes. In case of completeness, the result of visual inspection shows that all the lines are detected and modeled well as compare with the original point clouds. The overall processes are fully automated and the methods manage any state of railroad wires efficiently.