Jung-Chul Lee

Development of moving target detection based on image processing techniques

In order to effectively detect moving targets in strong noise conditions, we proposed an image processing method based on wavelet and Hough transform (HT) for multiple moving targets detection. Firstly, the noise is removed from the received signal by the wavelet technique. We propose an improved wavelet threshold function. The new threshold function not only reduces constant error of soft thresholding but also improve the discontinuity of hard thresholding. Secondly, the image processing technique of the Hough transform is used. The benefits of this method include improved performance of detection, implementation flexibility, which indicates the effectiveness and robustness of the algorithm.

Drone Flight Path for Countacting of Industry Disaster

Drone is currently used for wide application areas in our real life. Also it performs more important functions. We propose a method of drone operation system for the prevention of industrial disaster. In normal operation of drone system the drone monitors the industrial sites according to the planned flight path with acquiring the monitored images and send the image information to the server. The server analyzes and compares the images to DB information by calculating the similarity based on the threshold. Then the system decides whether the industrial sites has problems or not. If the abnormal condition is occurred, the drone change the flight path to abnormal flight path and keep monitoring the industrial sites with measuring the air status by sensors and sends all information to server system on the ground. If the emergency case is occurred, drone approaches the closest position of accident points and acquiring the all information and send them to server and 119 center.

Design and implementation of an automated monitoring system

One of the main limitations of existing monitoring systems is their dependency on the continuous recording of video data. As a result, the system consumes huge power and needs large memory to store this data. The aim of this paper is to present an automated monitoring system that can save memory, as well as measure the target distance precisely based on the motion sensors and ultrasonic sensor. The target is detected by motion sensors and then an ultrasonic sensor is used to measure the target distance. The cross-correlation technique is used to calculate the distance of targets using ultrasonic signal. To obtain high measuring accuracy, noise reduction technique and temperature effect on velocity have been adopted. A series of real-world experiments are conducted with different targets and target positions. The experimental results show that using a noise reduction technique and temperature compensation improve the accuracy of the designed system.

A New Method for Improving the Detection Capability of RADAR in the Presence of Noise

A RADAR system deals with many different and diverse problems for the last few decades. The detection capability of radar is one of the most important factors. The main objective of radar target detection is to improve probability of detection while reducing probability of a false alarm at the same time. To improve the probability of detection of moving target, a new approach is proposed in this paper using wavelet and Hough transforms. The wavelet de-noising technique is used to remove noise from received signal. Then the image processing technique of the Hough transform is used to detect moving target. To reduce the noises form received signal, we propose a new wavelet threshold function that reduces constant error of soft thresholding and improves the discontinuity of hard thresholding. We present performances of our method on a basis of the new thresholding technique and compare with traditional method. It is shown that detection performance of proposed method is superior to that obtained through traditional method.

Development of a Flute Self-Learning Tool Using an Electronic Flute and PC Software

In this paper, we propose a self-learning tool for the flute performance using PC-based software and an external electronic flute instrument. This tool provides information how to play and supports interaction for the exercise. Our software uses templates and descriptors to specify the window forms, contents type, and contents substance which can be easily modified by the user to match the contents to his level. We implemented a self-learning tool and our feasibility tests showed its validity for the beginner to learn playing flute and to improve the learning efficiency.