• Journal of Institute of Control, Robotics and Systems
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• v.3 no.4
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• pp.406-414
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• 1997

A real-time inspection system is developed using line scan cameras. Several improved algorithms are proposed for real-time detection of defects in this automated inspection system. The major improved algorithms include the preprocessing, the threshold decision, and the clustering algorithms. The preprocessing algorithms are for exact binarization and the threshold decision algorithm is for fast detection of defects in 1-D binary images. The clustering algorithm is also developed for fast classifying of the defects. The system is applied to PCBs(Printed Circuit Boards) inspection. The typical defects in PCBs are pits, dent, wrinkle, scratch, and black spots. The results show that most defects are detected and classified successfully.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.3 s.33
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• pp.87-94
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• 2005

3D positional information of lane can be automatically calculated tv combining GPS data, IMU data if coordinates of lane centers are given. The Road Safety Survey and Analysis Vehicle(RoSSAV) is currently under development to analyze three dimensional safety and stability of roads. RoSSAV has GPS and IMU sensors to get positional information of the vehicle and two road-facing CCD cameras for extraction of lane coordinates. In this paper, we develop technology that automatically detects centers of lanes from the road-facing cameras of RoSSAV. The proposed algorithm defines line-support regions by grouping pixels with similar edge orientation and magnitude together and extracts a line from each line support region by planar fitting. Then if extracted lines and the region in-between satisfy the criteria of brightness and width, we decide this region as lane. The proposed algorithm was more precise and stable than the previously proposed algorithm based on brightness threshold method. Experiments with real road scenes confirmed that lane was effectively extracted by the proposed algorithm.

• ETRI Journal
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• v.29 no.4
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• pp.411-420
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• 2007

The steady evolution of mapping technology is leading to an increasing availability of multi-sensory geo-spatial datasets, such as data acquired by single-head frame cameras, multi-head frame cameras, line cameras, and light detection and ranging systems, at a reasonable cost. The complementary nature of the data collected by these systems makes their integration to obtain a complete description of the object space. However, such integration is only possible after accurate co-registration of the collected data to a common reference frame. The registration can be carried out reliably through a triangulation procedure which considers the characteristics of the involved data. This paper introduces algorithms for a multi-primitive and multi-sensory triangulation environment, which is geared towards taking advantage of the complementary characteristics of spatial data available from the above mentioned sensors. The triangulation procedure ensures the alignment of involved data to a common reference frame. The devised methodologies are tested and proven efficient through experiments using real multi-sensory data.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.659-663
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• 2009

In this paper, we propose a rectification method that can convert ray space data obtained by controlled camera array to ideal data. Here, Ideal data is obtained by getting longitudinal and transversal epipolar line between cameras vertical and horizontal. However it is actually difficult to arrange cameras strictly because we arrange cameras by hand. As conventional method, we have use camera-calibration method. But if we use this method there are some errors on the output image. When we generate arbitrary viewpoint images this error is critical problem. We focus attention on ideal trajectory of characteristic point. And to minimize the error directly we parallelize the real one. And we showed usefulness of proposed technique. Then using the proposed technique, we were successful reducing the error to less than 0.5 pixels.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.15 no.2
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• pp.185-193
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• 1997

While close range photogrammetry has been widely applied for static deformation analysis, video cameras have many characteristics that make them the sensors of choice for dynamic analysis of rapidly changing situations. They also have limitations. The aim of this research is to explore the potential of a video system for monitoring dynamic objects. A pilot system consists of two camcorders, VCR, and PC with frame grabber. To estimte the performance of this system for moving objects, a car was imaged covering several phases when starting to drive. The sequential images of a moving car were recorded on VCR. 15 images per second were digitized in an off-line mode by frame grabber. The image coordinates of targets attached to the rear bumper of a car were acquired by IDRISI, and the object coordinates were derived based on DLT. This research suggests that home video cameras, PC, and photogrammetric principles are promising tools for monitoring of the moving objects and vibrations as well as other time dependent situations.

• Korean Journal of Geomatics
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• v.4 no.1
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• pp.23-30
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• 2004

This study aims to establish interior orientation for various types of sensors including frame cameras, panoramic cameras, line cameras, and whisk-broom scanners. To do so, this study suggests the classification of components of interior orientation of which elements are different according to the sensors. This is entailed by incorporation of sensor characteristics into mathematical models of interior orientation parameters are suggested for being used as guidelines in recovering systematic distortions. Finally, the potential errors resulted from the assumption of regarding sensor model of whisk-broom scanner model as that of push-broom scanner are discussed.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_3
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• pp.1191-1197
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• 2022

Recently, many studies have been conducted to utilize the digital aerial photogrammetry method in the field of cadastral surveying. The representative models of digital cameras currently used for aerial photogrammetry are classified into line-type and convex-type cameras, so the representative models were selected and analyzed. The purpose of this study was to analyze whether the accuracy suggested by the cadastral survey enforcement rules was satisfied by comparing the orthogonal and ortho image performance. As a result, there were some representative false points that exceeded the acceptable range, but the results extracted from most of the images were shown to satisfy the acceptable range. Therefore, it can be said that the application of digital aerial photogrammetry to the cadastral field in the technical aspect has sufficient potential.

• ETRI Journal
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• v.32 no.5
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• pp.729-739
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• 2010

Due to the rapid development of mobile devices equipped with cameras, instant translation of any text seen in any context is possible. Mobile devices can serve as a translation tool by recognizing the texts presented in the captured scenes. Images captured by cameras will embed more external or unwanted effects which need not to be considered in traditional optical character recognition (OCR). In this paper, we segment a text image captured by mobile devices into individual single characters to facilitate OCR kernel processing. Before proceeding with character segmentation, text detection and text line construction need to be performed in advance. A novel character segmentation method which integrates touched character filters is employed on text images captured by cameras. In addition, periphery features are extracted from the segmented images of touched characters and fed as inputs to support vector machines to calculate the confident values. In our experiment, the accuracy rate of the proposed character segmentation system is 94.90%, which demonstrates the effectiveness of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.10
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• pp.822-831
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• 2003

A computer-vision based pipe-inspection algorithm is developed. The algorithm uses the modified Hough transformation and a line-scanning approach to identify the edge line and the radius of the pipe image, from which the eccentricity and dimension of the pipe-end is calculated. Line and circle detection was performed using Laplace operator with input image, which are acquired from the front and side cameras. In order to minimize the memory usage and the processing time, a clustering method with the modified Hough transformation is introduced for line detection. The dimension of inner and outer radius of pipe is calculated by the proposed line-scanning method. The method scans several lines along the X and Y axes, calculating the eccentricity of inner and outer circle, by which pipes with wrong end-shape can be classified and removed.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.98-102
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• 1988

A simple look and move type navigation algorithm with obstacle avoidance was implemented on a mobile robot equipped with two cameras. The robot gets a difference of two images from each camera and detects the position represented on the horizontal line and width of each obstacle in a certain distance. The obtained informations of obstacles are used to select a next intermediate point and to plan a path to it. Robot motion is simplified to straight line motion and rotation.