• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.12
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• pp.122-130
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• 2010

This paper presents an active ranging system based on laser structured-light image. The structured-light image processing is computationally efficient in comparison with the conventional stereo image processing, since the burdensome correspondence problem is avoidable. In order to achieve robustness against environmental illumination noise, an efficient image processing algorithm, i.e., integration of difference images with structured-light modulation is proposed. Distance equation from the measured structured light pixel distance and system parameter calibration are addressed in this paper. Experiments and analysis are carried out to verify performance of the proposed ranging system.

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

• The Journal of the Acoustical Society of Korea
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• v.21 no.5
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• pp.471-477
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• 2002

Recently, lip-reading has been studied actively as an auxiliary method of automatic speech recognition(ASR) in noisy environments. However, almost of research results were obtained based on the database constructed in indoor condition. So, we dont know how developed lip-reading algorithms are robust to dynamic variation of image. Currently we have developed a lip-reading system based on image-transform based algorithm. This system recognize 22 words and this word recognizer achieves word recognition of up to 53.54%. In this paper we present how stable the lip-reading system is in environmental variance and what the main variant factors are about dropping off in word-recognition performance. For studying lip-reading robustness we consider spatial valiance (translation, rotation, scaling) and illumination variance. Two kinds of test data are used. One Is the simulated lip image database and the other is real dynamic database captured in car environment. As a result of our experiment, we show that the spatial variance is one of degradations factors of lip reading performance. But the most important factor of degradation is not the spatial variance. The illumination variances make severe reduction of recognition rates as much as 70%. In conclusion, robust lip reading algorithms against illumination variances should be developed for using lip reading as a complementary method of ASR.