• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.995-1000
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• 1999

This paper presents a optic system and a visual inspection algorithm looking for solder joint defects of J-lead chip which are more integrate and smaller than ones with Gull-wing on PCBs(Printed Circuit Boards). The visual inspection system is composed of three sections : host PC, imaging and driving parts. The host PC part controls the inspection devices and executes the inspection algorithm. The imaging part acquires and processes image data. And the driving part controls XY-table for automatic inspection. In this paper, the most important five features are extracted from input images to categorize four classes of solder joint defects in the case of J-lead chip and utilized to a back-propagation network for classification. Consequently, good accuracy of classification performance and effectiveness of chosen five features are examined by experiment using proposed inspection algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.7
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• pp.26-35
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• 1998

This paper presents a visual inspection algorithm looking for solder joint defects of IC chips on PCBs (Printed Circuit Boards). In this algorithm, seven features are proposed in order to categorize the solder joints into four classes such as normal, insufficient, excess, and no solder, and optimal back-propagation network is determined by error evaluation which depend on the number of neurons in hidden and out-put layers and selection of the features. In the end, a good accuracy of classification performance, an optimal determination of network structure and the effectiveness of chosen seven features are examined by experiment using proposed inspection algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.91.4-91
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• 2001

In this paper, a development of the sensor fusion algorithm for a visual control of mobile robot is presented. The output data from the visual sensor include a time-lag due to the image processing computation. The sampling rate of the visual sensor is considerably low so that it should be used with other sensors to control fast motion. The main purpose of this paper is to develop a method which constitutes a sensor fusion system to give the optimal state estimates. The proposed sensor fusion system combines the visual sensor and inertial sensor using a modified Kalman filter. A kind of multi-rate Kalman filter which treats the slow sampling rate ...

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.12
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• pp.984-993
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• 2003

In Gravure printing process, there are a lot of printing errors caused by expansion and contraction of printing materials and difficulty of printing of small letters, accordingly we cannot detect those errors with eyes. In this paper, we describe the algorithm which can detect small errors automatically in Gravure printing process and a real-time detection system adopting the algorithm. We present the Perimetric Mask algorithm that can eliminate tiny errors occurring near the contour of printing objects to achieve accurate inspection, and also construct an algorithm utilizing symmetry transform which can emphasize tiny errors to make a robust inspection system. We have made a system running in real-time and verified the efficiency of the algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.4
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• pp.321-329
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• 2015

This paper addresses a new algorithm for a stereo visual odometry to measure the ego-motion of a vehicle. The new algorithm introduces an inlier grouping method based on Delaunay triangulation and vanishing point computation. Most visual odometry algorithms rely on RANSAC in choosing inliers. Those algorithms fluctuate largely in processing time between images and have different accuracy depending on the iteration number and the level of outliers. On the other hand, the new approach reduces the fluctuation in the processing time while providing accuracy corresponding to the RANSAC-based approaches.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.743-744
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• 2008

By using DirectX technology, an improved Visual Monitoring System implemented in this paper. The proposed Visual Monitoring System is developed based on the S3C2440 processor. The Windows CE 5.0 is adopted as an operating system, and Visual Monitoring System transfer image 15 frame per second using UDP/IP and by using AdaBoost Algorithm, detect face region and save face image.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.4
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• pp.369-375
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• 2008

The kinematics and control problem of a visual alignment system is investigated, which plays a crucial role in the fabrication process of flat panel displays. The first solution is the inverse kinematics of a 4PPR parallel alignment mechanism. It determines the driving distance of each joint to compensate the misalignment between mask and panel. Second, an efficient vision algorithm for fast alignment mark recognition is suggested, where by extracting essential feature points to represent the geometry of a mark, the geometric template matching enables much faster object recognition comparing with the general template matching. Finally, the overall visual alignment process including the kinematic solution, vision algorithm, and joint control is implemented and experimental results are given.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3401-3420
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• 2018

Pixel expansion and contrast are two major performance parameters for visual cryptography scheme (VCS), which is a type of secret image sharing. Random Grid (RG) is an alternative approach to solve the pixel expansion problem. Chen and Tsao proposed the first (k, n) RG-based VCS, and then Guo et al., Wu et al., Shyu, and Yan et al. significantly improved the contrast in recent years. However, the investigations on improving the contrast of threshold RG-based VCS are not sufficient. In this paper, we develop a contrast-improved algorithm for (k, n) RG-based VCS. Theoretical analysis and experimental results demonstrate that the proposed algorithm outperformers the previous threshold algorithms with better visual quality and a higher accuracy of contrast.

• The Journal of the Acoustical Society of Korea
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• v.20 no.3
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• pp.63-69
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• 2001

A corpus-based lip sync algorithm for synthesizing natural face animation is proposed in this paper. To get the lip parameters, some marks were attached some marks to the speaker's face, and the marks' positions were extracted with some Image processing methods. Also, the spoken utterances were labeled with HTK and prosodic information (duration, pitch and intensity) were analyzed. An audio-visual corpus was constructed by combining the speech and image information. The basic unit used in our approach is syllable unit. Based on this Audio-visual corpus, lip information represented by mark's positions was synthesized. That is. the best syllable units are selected from the audio-visual corpus and each visual information of selected syllable units are concatenated. There are two processes to obtain the best units. One is to select the N-best candidates for each syllable. The other is to select the best smooth unit sequences, which is done by Viterbi decoding algorithm. For these process, the two distance proposed between syllable units. They are a phonetic environment distance measure and a prosody distance measure. Computer simulation results showed that our proposed algorithm had good performances. Especially, it was shown that pitch and intensity information is also important as like duration information in lip sync.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2529-2551
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• 2022

Visual servoing (VS) based on the Kalman filter (KF) algorithm, as in the case of KF-based image-based visual servoing (IBVS) systems, suffers from three problems in uncalibrated environments: the perturbation noises of the robot system, error of noise statistics, and slow convergence. To solve these three problems, we use an IBVS based on KF, African vultures optimization algorithm enhanced extreme learning machine (AVOA-ELM), and fuzzy logic (FL) in this paper. Firstly, KF online estimation of the Jacobian matrix. We propose an AVOA-ELM error compensation model to compensate for the sub-optimal estimation of the KF to solve the problems of disturbance noises and noise statistics error. Next, an FL controller is designed for gain adaptation. This approach addresses the problem of the slow convergence of the IBVS system with the KF. Then, we propose a visual servoing scheme combining FL and KF-AVOA-ELM (FL-KF-AVOA-ELM). Finally, we verify the algorithm on the 6-DOF robotic manipulator PUMA 560. Compared with the existing methods, our algorithm can solve the three problems mentioned above without camera parameters, robot kinematics model, and target depth information. We also compared the proposed method with other KF-based IBVS methods under different disturbance noise environments. And the proposed method achieves the best results under the three evaluation metrics.