• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.2
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• pp.40-46
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• 2011

This paper proposes a real-time face detection and tracking system that uses neural oscillators which can be applied to access regulation system or control systems of user authentication as well as a new algorithm. We study a way to track faces using the neural oscillatory network which imitates the artificial neural net of information handing ability of human and animals, and biological movement characteristic of a singular neuron. The system that is suggested in this paper can broadly be broken into two stages of process. The first stage is the process of face extraction, which involves the acquisition of real-time RGB24bit color video delivering with the use of a cheap webcam. LEGION(Locally Excitatory Globally Inhibitory)algorithm is suggested as the face extraction method to be preceded for face tracking. The second stage is a method for face tracking by discovering the leader neuron that has the greatest connection strength amongst neighbor neuron of extracted face area. Along with the suggested method, the necessary element of face track such as stability as well as scale problem can be resolved.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.2
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• pp.179-186
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• 2017

Because facial asymmetry is caused by various causes, the cause analysis is important and quantitative index is needed to the evaluation. In this study, we applied the Nottingham Grading System that was used as a quantitative index to evaluate the facial paralysis by tracking the markers through the image processing and calculating the distance between the markers with images obtained by using the webcam, to evaluate facial asymmetry. The existing Nottingham Grading System has a problem of causing a measurement error in the specific case because the left and right are compared by summing the distance change between the feature points of the face part according to the change of the facial expression. We compared the case of the facial asymmetry and case of normal subject by using the existing Nottingham Grading System and the improved Nottingham grading system. In the existing Nottingham Grading System, case of facial asymmetry and case of facial symmetry were 99.0% and 95.0% respectively in the normal range, but the improved Nottingham Grading System showed facial asymmetry case was 74.0% and facial symmetrical case was 93.2%. The results of experiment show that the improved Nottingham Grading System allows detailed evaluation of each site and improved the problem of the Nottingham Grading System for specific cases.

• The KIPS Transactions:PartB
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• v.19B no.4
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• pp.225-230
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• 2012

In this paper, a blind person using a white cane as an adjunct of the things available sensing technology has been implemented. Sensing technology to implement things ultrasonic sensors and a webcam was used to process the data from the server computer. Ultrasonic sensors detect objects within 4meter people distinguish between those things that if the results based on the results will sound off. In this study, ultrasonic sensors, object recognition and human perception with the introduction of techniques and technologies developed for detecting objects in the lives of the visually impaired is expected to be greater usability.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.12
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• pp.1833-1840
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• 2013

A golf ball collecting robot in a golf ball driving range has been recently required because it is safer and more economic than a human being. In this paper, the golf ball recognition and distance estimation system based on a neural network and OpenCV is developed for the robot. The simulation results show that the recognition ratio is over 87% for the distance of less than 120cm and accurate rate for distance estimation is over 85% for golf balls in 30-180cm from a webcam.

• Korean Journal of Artificial Intelligence
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• v.5 no.2
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• pp.15-25
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• 2017

Recently, technologies are being developed to recognize and authenticate users using bioinformatics to solve information security issues. Biometric information includes face, fingerprint, iris, voice, and vein. Among them, face recognition technology occupies a large part. Face recognition technology is applied in various fields. For example, it can be used for identity verification, such as a personal identification card, passport, credit card, security system, and personnel data. In addition, it can be used for security, including crime suspect search, unsafe zone monitoring, vehicle tracking crime.In this thesis, we conducted a study to recognize faces by detecting the areas of the face through a computer webcam. The purpose of this study was to contribute to the improvement in the accuracy of Recognition of Face Based on CNN Algorithms. For this purpose, We used data files provided by github to build a face recognition model. We also created data using CNN algorithms, which are widely used for image recognition. Various photos were learned by CNN algorithm. The study found that the accuracy of face recognition based on CNN algorithms was 77%. Based on the results of the study, We carried out recognition of the face according to the distance. Research findings may be useful if face recognition is required in a variety of situations. Research based on this study is also expected to improve the accuracy of face recognition.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.696-699
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• 2018

This paper introduces a system that enables pupillary tracing and communication with patients with amyotrophic lateral sclerosis (ALS) who can not move free. Face and pupil are tracked using OpenCV, and eye movements are detected using DE1-SoC board. We use the webcam, track the pupil, identify the pupil's movement according to the pupil coordinate value, and select the character according to the user's intention. We propose a system that can use relatively low development cost and FPGA can be reusable, and can select a text easily to mobile phone by using Bluetooth.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.4
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• pp.691-700
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• 2017

This paper describes the design and implementation of automatic braille converter based on image processing for a person who is visually impaired. The conversion algorithm based on the image processing converts the input image obtained by the web-cam to binary image, and then calculates the cross-correlation with the stored character pattern image by labeling the character area and converts the character pattern image into the corresponding braille. The computer simulations showed that the proposed algorithm showed 95% and 91% conversion success rates for numerals and alphabets printed on A5 paper. The prototype test implemented by the servo motor using Arduino confirmed 89%, conversion performance. Therefore, we confirmed the feasibility of the automatic braille transducer.

• 한국HCI학회:학술대회논문집
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• 2008.02b
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• pp.60-63
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• 2008

The sony Eytoy is developed on Playstation 2 using webcam for detecting human. A user see his appearance in television and become real gamer in the game. It is very different interface compared with ordinary video game which uses joystick. Although Eyetoy already was made for commercial products but the interface method still is interesting and can be added with many techniques like gesture recognition. In this paper, we have developed game interface with image processing for human hand and face detection and with game graphic module. And we realize one example game for busting balloons and demonstrated the game interface abilities. We will open this project for other developers and will be developed very much.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.4
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• pp.237-241
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• 2011

Stable operation of an industry crane becomes more important as current industry facilities become larger and operate at higher speeds. This paper proposes implementing a system for monitoring moving objects within safety lines of an industry crane by camera. The cost of implementing such a system is low, since it requires only a webcam and notebook computer. The detection algorithm of moving objects uses the feature extraction method by image differential histograms. The proposed system is robust to variations in the weather and environment. The area of the inside safety lines is considered and shadow removal algorithm is used for good performance of the system. The system is valuable for practical applications in the industry.