• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3666-3671
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• 2012

We evaluate the face detection and recognition of depth image that is obtained by infrared range sensor. and Face recognition was usually focused on accuracy aspect but it is not enough to evaluate the performance in testing for real world application. In this paper, we evaluate the overall performance like accuracy, training, test speed and memory use for the well known face recognition algorithm like PCA, LDA, ICA and SVM. This experiment evaluate the good results of depth and colored depth image compatible with the colored image although the file size of depth and colored depth image is 30%~40% less than the colored image. Whereas, LDA got the good accuracy performance next to the SVM and also shows the good performance in speed and the amount of memory.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.101-108
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• 2024

AI-OCR (Artificial Intelligence Optical Character Recognition) combines OCR technology with Artificial Intelligence to overcome limitations that required human intervention. To enhance the performance of AI-OCR, training on diverse data sets is essential. However, the recognition rate declines when image colors have similar brightness levels. To solve this issue, this study employs Homomorphic filtering as a preprocessing step to clearly differentiate color levels, thereby increasing text recognition rates. While Homomorphic filtering is ideal for text extraction because of its ability to adjust the high and low frequency components of an image separately using a gamma value, it has the downside of requiring manual adjustments to the gamma value. This research proposes a range for gamma threshold values based on tests involving image contrast, brightness, and entropy. Experimental results using the proposed range of gamma values in Homomorphic filtering suggest a high likelihood for effective AI-OCR performance.

• Journal of Korea Multimedia Society
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• v.18 no.4
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• pp.557-564
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• 2015

There are many prior studies for more natural Human-Computer Interaction. Until now, the efforts is continued in order to recognize motions in various directions. In this paper, we suggest a user-specific recognition by hit detection method using Kinect camera and human proportion. This algorithm extracts the user-specific valid recognition rage after recognizing the user's body initially. And it corrects the difference in horizontal position between the user and Kinect, so that we can estimate a action of user by matching cursor to target using only one frame. Ensure that efficient hand recognition in the game to take advantage of this method of suggestion.

• The Journal of Korea Robotics Society
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• v.3 no.1
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• pp.33-41
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• 2008

Based on object recognition technology, we present a new global localization method for robot navigation. For doing this, we model any indoor environment using the following visual cues with a stereo camera; view-based image features for object recognition and those 3D positions for object pose estimation. Also, we use the depth information at the horizontal centerline in image where optical axis passes through, which is similar to the data of the 2D laser range finder. Therefore, we can build a hybrid local node for a topological map that is composed of an indoor environment metric map and an object location map. Based on such modeling, we suggest a coarse-to-fine strategy for estimating the global localization of a mobile robot. The coarse pose is obtained by means of object recognition and SVD based least-squares fitting, and then its refined pose is estimated with a particle filtering algorithm. With real experiments, we show that the proposed method can be an effective vision- based global localization algorithm.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.5
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• pp.10-16
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• 1985

In this paper, a computer vision system, which catches printed music score image using CCTV camera and microcomputer, and then recognizes the image and performs tar music with speaker, is discussed. Integral projection method is adopted for feature detection and recognition of the music score image. The range of recognition is con(ined to staffs, perpen-dicular lines and musical notes including chord notes among the various kinds of elements of music score. The practical recognition algorithm considering noises, the preprocessing processes getting rid of noises are also showed, and simple hardware system playing chord is made, In the results, good recognition ratio and performance are obtained.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.9
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• pp.1171-1180
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• 1995

In this paper, we present a 3-D object recognition system in which the 3-D Hough transform domain is employed to represent the 3-D objects. In object modeling step, the features for recognition are extracted from the CAD models of objects to be recognized. Since the approach is based on the CAD models, the accuracy and flexibility are greatly improved. In matching stage, the sensed image is compared with the stored model, which is assumed to yield a distortion (location and orientation) in the 3-D Hough transform domain. The high dimensional (6-D) parameter space, which defines the distortion, is decomposed into the low dimensional space for an efficient recognition. At first we decompose the distortion parameter into the rotation parameter and the translation parameter, and the rotation parameter is further decomposed into the viewing direction and the rotational angle. Since we use the 3-D Hough transform domain of the input images directly, the sensitivity to the noise and the high computational complexity could be significantly alleviated. The results show that the proposed 3-D object recognition system provides a satisfactory performance on the real range images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.738-741
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• 2009

This research is concerned for improving the result of speech recognition under the noisy speech. We knew that spectral subtraction and recovery of valleys in spectral envelope obtained from noisy speech are more effective for the improvement of the recognition. In this research, the averaged spectral envelope obtained from vowel spectrums are used for the emphasis of valleys. The vocalic spectral information at lower frequency range is emphasized and the spectrum obtained from consonants is not changed. In simulation, the emphasis coefficients are varied on cepstral domain. This method is used for the recognition of noisy digits and is improved.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.5
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• pp.9-11
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• 2001

• Agricultural and Biosystems Engineering
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• v.2 no.2
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• pp.69-74
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• 2001

Detection of operation lines in farm works, object recognition and obstacle avoidance are essential pre-requisite technologies for unmanned agricultural machinery. A CCD camera, which has been largely used for these functions, is expensive and has difficulty in real-time signal processing. In this study, a laser range sensor was selected as the guiding vision for unmanned agricultural machinery such as a tractor. To achieve this capability, algorithms for distance measurement, signal filtering, object recognition, and obstacle avoidance were developed. Computer simulations were carried out to evaluate performance of the algorithms. Experiments were also conducted with various materials and shapes, Laser beam lost its intensity for poor reflective materials, resulting in less range value than actual, so a compensation technique was considered to be necessary. Object detection system was fabricated on an agricultural tractor and the performance was evaluated. As test result for obstacle detection and avoidance in field, to detect and avoid obstacle for path finding with guiding system for unmanned agricultural machinery was enable.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.4 s.97
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• pp.37-45
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• 1999

Many automated welding equipment are used in the industry. However, there are some problems to get quality welds because of the geometric error, thermal distortion, and incorrect joint fit-up. These factors can make the gap between base plates in case of a thick plate welding. The welding product with the quality welds can not be obtained without consideration of the gap. In this paper, the robot path and welding conditions are modified to get the quality weld by detecting the position and size of the gap. In this work, a low-priced laser range sensor is used. The 3-dimensional information is obtained using the motion of a robot, which holds a laser range sensor. The position and size of the gap is calculated using signal processing of the measured 3-dimensional information of joint profile geometry. The data measured by a laser range sensor is segmented by an iterative end point method. The segmented data is optimized by the least square method. The existence of gap is detected by comparing the data with the segmented shape of template. The effects of robot measuring speed and gap size are also tested. The recognizability fo the gap is verified as good by comparing the real joint profile and the calculated joint profile using the signal processing.