• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4489-4501
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• 2014

We propose a novel lane detection method based on classification in image sequences. Both structural and statistical features of the extracted bright shape are applied to the neural network for finding correct lane marks. The features used in this paper are shown to have strong discriminating power to locate correct traffic lanes. The traffic lanes detected in the current frame is also used to estimate the traffic lane if the lane detection fails in the next frame. The proposed method is fast enough to apply for real-time systems; the average processing time is less than 2msec. Also the scheme of the local illumination compensation allows robust lane detection at nighttime. Therefore, this method can be widely used in intelligence transportation systems such as driver assistance, lane change assistance, lane departure warning and autonomous vehicles.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1012-1014
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• 1997

This paper introduces wavelets and shows that they may be efficient and useful for the detection of general faults in power system. The wavelet transform of a signal consists in measuring the "similarity" between the signal and a set of translated and scaled versions of a "mother wavelet". The "mother wavelet" is a chosen fast decaying oscillation function. A number of mother wavelet for signal analysis have been proposed and some of them are in use in fault detection. However, the performance of fault detection depend on used mother wavelet. In the present paper a comparative evaluation of different mother wavelets for low impedance fault detection is performed. The discussion is focused in well-known mother wavelet based wavelet transform. Several families of wavelets are used to analyse transient earth fault signals in a 345kV model system as generated by EMTP.

• ETRI Journal
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• v.41 no.5
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• pp.560-573
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• 2019

Two supervised learning algorithms, a basic neural network and a long short-term memory recurrent neural network, are applied to traffic including DDoS attacks. The joint effects of preprocessing methods and hyperparameters for machine learning on performance are investigated. Values representing attack characteristics are extracted from datasets and preprocessed by two methods. Binary classification and two optimizers are used. Some hyperparameters are obtained exhaustively for fast and accurate detection, while others are fixed with constants to account for performance and data characteristics. An experiment is performed via TensorFlow on three traffic datasets. Three scenarios are considered to investigate the effects of learning former traffic on sequential traffic analysis and the effects of learning one dataset on application to another dataset, and determine whether the algorithms can be used for recent attack traffic. Experimental results show that the used preprocessing methods, neural network architectures and hyperparameters, and the optimizers are appropriate for DDoS attack detection. The obtained results provide a criterion for the detection accuracy of attacks.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11c
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• pp.525-532
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• 2000

A new spectroscopic method for pesticide residues detection on agricultural products was developed. The general determination methods are high performance liquid chromatography (HPLC), gas chromatography (GC) or GC-mass spectrometry. They have provided relatively good detection limit and accuracy with complicated and time-consuming (5hrs above) procedures. In addition freshness is very important for evaluating qualities of agricultural products. This requires a simple and fast method for detection of pesticides. Reflectance, transmittance and fluorescence spectrometry of pesticides were tested using UV range because most of pesticides contain conjugation band in the molecular structures. Fluorescence spectrometry showed better sensitive to detect pesticide residues than did reflectance and transmittance spectrometry. Intensity and shape of fluorescence spectra showed different patterns with different structures of pesticides. Detection limit for fluorescence spectrometry was 0.1 ppm to 10 ppm depending on the structures of pesticides. Application of fluorescence spectrometry appears to be an easy method for detection of pesticide residues on agricultural products.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.343-350
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• 2002

A scene change detection which involves finding a cut between two consecutive shots is an important step for video indexing and retrieval. This paper proposes an algorithm for fast and accurate detection of abrupt scene changes in an MPEG compressed domain with minimal decoding requirements arid computational effort. The proposed method compares two successive DC images of I-frames for finding the GOP (group of picture) which contain a scene change and uses macroblock-coded type information contained in B-frames to detect the exact frame where the scene change occurred. The experiment results demonstrate that the proposed algorithm has better detection performance, such as precision and recall rate, than the existing method using all DC images. The algorithm has the advantage of speed, simplicity and accuracy. In addition, it requires less amount of storage.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.3
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• pp.107-112
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• 2018

In this paper, optical flow based keypoint detection and tracking technique is proposed for the collaboration between flying drone with vision system and ground robots. There are many challenging problems in target detection research using moving vision system, so we combined the improved FAST algorithm and Lucas-Kanade method for adopting the better techniques in each feature detection and optical flow motion tracking, which results in 40% higher in processing speed than previous works. Also, proposed image binarization method which is appropriate for the given marker helped to improve the marker detection accuracy. We also studied how to optimize the embedded system which is operating complex computations for intelligent functions in a very limited resources while maintaining the drone's present weight and moving speed. In a future works, we are aiming to develop collaborating smarter robots by using the techniques of learning and recognizing targets even in a complex background.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.119-128
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• 2014

In this paper, a fast human detection method using adaptive UV-histogram and template matching is proposed. The proposed method improves the detection rate in the scene of complex environment. The method firstly generates U-histogram to extract human candidates and adaptively generates V-histogram for each labled U-histogram, thus it could extract humans correctly, which was impossible in the previous method. The method tries to match the human candidates with the adaptively sized omega shape template to the focal length and distance in order to improve the detection accuracy. It also detects false positives by rematching the template with accumulated foreground images and hence is robust to the occlusion. Experimental results showed that the proposed method has superior performance to the Bae's method in the complex environment with about 15% improvement in precision and 80% in recall and has 20 times faster processing time than Xia's method.

• Journal of IKEEE
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• v.10 no.1 s.18
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• pp.87-95
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• 2006

This paper presents the analyses of the effect of inserting border lines between different color regions on edge detection in color codes, and is not intended to present any new algorithm for color-code recognition. With its role to complement the RFID (radio frequency identification) and the wide and fast spread of digital cameras, an interest on color codes is fast increasing. However, the severe distortion of colors in obtained images prohibits color codes from expanding their applications. To reduce the effect of color distortion it is desirable to process the whole pixels in each color region statistically, instead of relying on some pixels sampled from the region. This requires segmentation, and the segmentation usually requires edge detection. To help detect edges not disconnected, we inserted border lines of the width of two pixels between adjacent color regions. Two colors were used for the border lines: one consisting of white pixels, and the other black pixels. The edge detection was performed on images with either of the two kinds of border lines inserted, and the results were compared to results without inserted border lines. We found that inserting black border lines degraded edge detection by causing zipper effect while inserting white border lines improved it compared to the cases without inserted border lines.

• Journal of KIISE:Software and Applications
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• v.32 no.12
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• pp.1247-1259
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• 2005

This paper proposes a real-time face recognition system which detects multiple faces from low resolution video such as web-camera video. Face recognition system consists of the face detection step and the face classification step. At First, it finds face region candidates by using AdaBoost based object detection method which have fast speed and robust performance. It generates reduced feature vector for each face region candidate by using principle component analysis. At Second, Face classification used Principle Component Analysis and multi-SVM. Experimental result shows that the proposed method achieves real-time face detection and face recognition from low resolution video. Additionally, We implement the auto-tracking face recognition system using the Pan-Tilt Web-camera and radio On/Off digital door-lock system with face recognition system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.1103-1105
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• 2015

Leaked Radioactive source in nuclear power station, radiation related facilities and the aging nuclear power plant for the dismantling must need to detect and remove early to prevent major accidents. In this paper, we implemented a single sensor-based gamma-ray detectors stereo which can provide the distance to the radiation source, a direction and doserate information for fast and efficient decontamination work the radiation source. And we have carried out an algorithm development for high-speed detection of the detection equipment. Two detectors are required for stereo structure for obtaining the distance information of the radioactive source, but we designed the only sensor-based detection device for the weight reduction. We have extracted the region of interest and obtained the distance calculation result and distribution of radiation source in order to minimize a stereo image acquisition time. Detection time of the algorithm showed a shorter time of about 41%.