• International Journal of Contents
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• v.10 no.4
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• pp.63-68
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• 2014

In this paper, we propose a smart system that can optically recognize a music score within a document and can play the music after recognition. Many historic handwritten documents have now been digitalized. Converting images of a music score within documents into digital files is particularly difficult and requires considerable resources because a music score consists of a 2D structure with both staff lines and symbols. The proposed system takes an input image using a mobile device equipped with a camera module, and the image is optimized via preprocessing. Binarization, music sheet correction, staff line recognition, vertical line detection, note recognition, and symbol recognition processing are then applied, and a music file is generated in an XML format. The Music XML file is recorded as digital information, and based on that file, we can modify the result, logically correct errors, and finally generate a MIDI file. Our system reduces misrecognition, and a wider range of music score can be recognized because we have implemented distortion correction and vertical line detection. We show that the proposed method is practical, and that is has potential for wide application through an experiment with a variety of music scores.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.5
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• pp.25-30
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• 2017

In this Paper, we Propose the Low-cost Obstacle Recognition System Utilizing the Ultrasonic Sensor. Developed Obstacle Recognition System can be used to Aid the Visually Impaired Person. The Existence of the Obstacle is Notified to the Person through the Embodied Electronic Vibration Motor. The Timing Difference from the Recognition to the Notification Indicates the Distance to the Obstacle. Pulsed Ultrasonic Signal Controlled by MCU is Utilized and the Reflected Pulse through the Obstacle gives the Developed System the Existence of the Obstacle and the Distance to the Object. Pulse is sent Repetitively to Improve the Detection Accuracy. Developed Apparatus gives 30 Degree of Detection Angle and 2cm-30cm of the Detection Range when the Apparatus is Tested under Normal Walking Environment.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.6
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• pp.577-583
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• 2011

Radar performance test is one of the major steps for radar system design. However, it is restricted by time and cost when radar performance tests are performed with opportunity targets. So various simulated target generators are developed and used to evaluate radar performance. To simulate the target's range, most of simulated target generators are developed with optical line or DRFM(Digital RF Memory) technique but there are many restrictions such as limit of range imitation and test scenario because of their original usage. In this paper, DDL(Digital Delay Line) module for development of simulated target generator is designed with precise range simulation and easily embodiment feature. And pulse recognition and delay gap detection technique are used to simulate the time delay without distortions. Developed DDL module performances are verified through their performance tests and test results are described in this paper.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.1
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• pp.160-164
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• 2005

The process of recognizing a vehicle involves detection of the vehicle, recognition of the vehicle model, and identification of the vehicle. The process of vehicle identification involves identification of the vehicle itself, such as by recognition of the license plate on the vehicle. In this paper the method involves the use of a beam splitter to divide incident rays into two directions, a transmitted beam and a reflected beam of different light intensities, and synthesizing two captured images using CCD devices from each beam, thus producing fluctuation-free images of a wide dynamic range even when the subject is moving. A prototype license plate recognition system was also developed using the experimental sensing device. The system achieved a 98.7% recognition rate on 466 images of moving vehicles, which demonstrates its effectiveness as a license plate recognition system.

• Journal of Sensor Science and Technology
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• v.33 no.4
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• pp.187-195
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• 2024

Light detection and ranging (LiDAR), a widely used sensor in mobile robots and autonomous vehicles, has its most important function as measuring the range of objects in three-dimensional space and generating point clouds. These point clouds consist of the coordinates of each reflection point and can be used for various tasks, such as obstacle detection and environment recognition. However, several processing steps are required, such as three-dimensional modeling, mesh generation, and rendering. Efficient data processing is crucial because LiDAR provides a large number of real-time measurements with high sampling frequencies. Despite the rapid development of controller computational power, simplifying the computational algorithm is still necessary. This paper presents a method for estimating the presence of curbs, humps, and ground tilt using range measurements from a single horizontal or vertical scan instead of point clouds. These features can be obtained by data segmentation based on linearization. The effectiveness of the proposed algorithm was verified by experiments in various environments.

• International journal of advanced smart convergence
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• v.8 no.4
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• pp.104-112
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• 2019

This study proposed a robust detection algorithm. It detects face more stably with respect to changes in light and rotation forthe identification of a face shape. The proposed algorithm uses face shape asinput information in a single camera environment and divides only face area through preprocessing process. However, it is not easy to accurately recognize the face area that is sensitive to lighting changes and has a large degree of freedom, and the error range is large. In this paper, we separated the background and face area using the brightness difference of the two images to increase the recognition rate. The brightness difference between the two images means the difference between the images taken under the bright light and the images taken under the dark light. After separating only the face region, the face shape is recognized by using the self-organization feature map (SOFM) algorithm. SOFM first selects the first top neuron through the learning process. Second, the highest neuron is renewed by competing again between the highest neuron and neighboring neurons through the competition process. Third, the final top neuron is selected by repeating the learning process and the competition process. In addition, the competition will go through a three-step learning process to ensure that the top neurons are updated well among neurons. By using these SOFM neural network algorithms, we intend to implement a stable and robust real-time face shape recognition system in face shape recognition.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.209-214
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• 2018

The subway, which is an urban railway, is the core of public transportation. Urban railways are always exposed to serious problems such as theft, crime and terrorism, as many passengers use them. Especially, due to the nature of urban railway environment, the scope of surveillance is widely dispersed and the range of surveillance target is rapidly increasing. Therefore, it is difficult to perform comprehensive management by passive surveillance like existing CCTV. In this paper, we propose the implementation, design method and object recognition algorithm for intelligent object recognition system in urban railway. The object recognition system that we propose is to analyze the camera images in the history and to recognize the situations where there are objects in the landing area and the waiting area that are not moving for more than a certain time. The proposed algorithm proved its effectiveness by showing detection rate of 100% for Selected area detection, 82% for detection in neglected object, and 94% for motionless object detection, compared with 84.62% object recognition rate using existing Kalman filter.

• KIISE Transactions on Computing Practices
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• v.22 no.4
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• pp.170-177
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• 2016

Character encoding is a method for changing a document to a binary document file using the code table for storage in a computer. When people decode a binary document file in a computer to be read, they must know the code table applied to the file at the encoding stage in order to get the original document. Identifying the code table used for encoding the file is thus an essential part of decoding. In this paper, we propose a method for detecting the character code of the given binary document file automatically. The method uses many techniques to increase the detection rate, such as a character code range detection, escape character detection, character code characteristic detection, and commonly used word detection. The commonly used word detection method uses multiple word database, which means this method can achieve a much higher detection rate for multi-language files as compared with other methods. If the proportion of language is 20% less than in the document, the conventional method has about 50% encoding recognition. In the case of the proposed method, regardless of the proportion of language, there is up to 96% encoding recognition.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.92-99
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• 2009

This paper established the range of the wavelength of traffic lights to detection the color of traffic lights and the color component segmentation with the range of the wavelength. Development of traffic light automatic discrimination system is consists of the color detection and the traffic lights recognition. In this thesis, it established the range of the wavelength of traffic lights to detection the color of traffic lights and the color segmentation with the range of the wavelength. By the segmentation, the traffic light colors(red, orange and green) can be detected and the background is changed into gray image. Next, we proposed the algorithm which can detect the area of traffic lights in the various surroundings with the wavelet transformation algorithm. Also, we proposed traffic lights recognition algorithm using between the edge operator and the Hausdorff distance algorithm based on CBIR(Content-based Image retrieval). Therefore, the proposed algorithm is more superior to the conventional algorithm by experimenting with the illumination including the traffic lights and the backgrounds with various images.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.12
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• pp.174-182
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• 2015

In this paper, we developed the small size RGB sensor that recognizes a long distance using a low-cost color sensor. Light receiving portion of the sensor was used as a camera lens for far distance recognition, and illuminating unit was increased the strength of the light by using a high-power white LED and a lens mounted on the reflector. RGB color recognition algorithm consists of the learning process and the realtime recognition process. We obtain a normalized RGB color reference data in the learning process using the specimens painted with target colors, and classifies the three colors using the Mahalanobis distance in recognition process. We apply the developed the RGB color recognition sensor to a prototype of the part classification system and evaluate the performance of its.