• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.4
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• pp.17-34
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• 2023

Camera trapping has been used as a non-invasive survey method that minimizes anthropogenic disturbance to ecosystems. Nevertheless, it is labor-intensive and time-consuming, requiring researchers to quantify species and populations. In this study, we aimed to improve the preprocessing of camera trapping data by utilizing an object detection algorithm. Wildlife monitoring using unmanned sensor cameras was conducted in a forested urban forest and a green space on a university campus in Cheonan City, Chungcheongnam-do, Korea. The collected camera trapping data were classified by a researcher to identify the occurrence of species. The data was then used to test the performance of the YOLO-X object detection algorithm for wildlife detection. The camera trapping resulted in 10,500 images of the urban forest and 51,974 images of green spaces on campus. Out of the total 62,474 images, 52,993 images (84.82%) were found to be false positives, while 9,481 images (15.18%) were found to contain wildlife. As a result of wildlife monitoring, 19 species of birds, 5 species of mammals, and 1 species of reptile were observed within the study area. In addition, there were statistically significant differences in the frequency of occurrence of the following species according to the type of urban greenery: Parus varius(t = -3.035, p < 0.01), Parus major(t = 2.112, p < 0.05), Passer montanus(t = 2.112, p < 0.05), Paradoxornis webbianus(t = 2.112, p < 0.05), Turdus hortulorum(t = -4.026, p < 0.001), and Sitta europaea(t = -2.189, p < 0.05). The detection performance of the YOLO-X model for wildlife occurrence was analyzed, and it successfully classified 94.2% of the camera trapping data. In particular, the number of true positive predictions was 7,809 images and the number of false negative predictions was 51,044 images. In this study, the object detection algorithm YOLO-X model was used to detect the presence of wildlife in the camera trapping data. In this study, the YOLO-X model was used with a filter activated to detect 10 specific animal taxa out of the 80 classes trained on the COCO dataset, without any additional training. In future studies, it is necessary to create and apply training data for key occurrence species to make the model suitable for wildlife monitoring.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.3
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• pp.27-35
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• 2002

A knowledge-based image retrieval technique is image searching methods using some features from the queried image. The materials in this study are automobile head lamps. The input data is composed of characters and images which have various pattern. The numbers, special symbols, and general letters are under the category of the character. The image informations are made up of the distribution of pixel data, statistical analysis, and state of pattern which are useful for the knowledge data. In this paper, we implemented a retrieval system for the scientific crime detection at traffic accident using the proposed multi knowledge-based image retrieval technique. The values for the multi knowledge-based image features were extracted from color and gray scale each. With this 22 features, we improved the retrieval efficiency about the color information and pattern information. Visual basic, crystal report and MS access DB were used for this application. We anticipate the efficient scientific detection for the traffic accident and the tracking of suspicious vehicle.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12C
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• pp.1044-1051
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• 2010

In this paper, we propose an efficient soft-output signal detection method for spatially multiplexed multiple input multiple output (MIMO) systems. The proposed method is based on the ordered successive interference cancellation (OSIC) algorithm, but it significantly improves the performance of the original OSIC algorithm by solving the error propagation problem. The proposed method combines this enhanced OSIC (ESIC) algorithm with a multiple ordering technique in a very efficient way. As a result, the log likelihood ratio (LLR) values can be computed by using a very small set of candidate symbol vectors. The proposed method has been implemented with a $0.13{\mu}m$ CMOS technology for a $4{\times}4$ 16-QAM MIMO system. The simulation and implementation results show that the proposed detector provides a very good solution in terms of performance and hardware complexity.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.4 s.304
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• pp.51-58
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• 2005

This paper proposes a robust scene change detection technique that uses the weighted chi-square test and the automated threshold-decision algorithms. The weighted chi-square test can subdivide the difference values of individual color channels by calculating the color intensities according to NTSC standard, and it can detect the scene change by joining the weighted color intensities to the predefined chi-square test which emphasize the comparative color difference values. The automated threshold-decision at algorithm uses the difference values of frame-to-frame that was obtained by the weighted chi-square test. At first, The Average of total difference values is calculated and then, another average value is calculated using the previous average value from the difference values, finally the most appropriate mid-average value is searched and considered the threshold value. Experimental results show that the proposed algorithms are effective and outperform the previous approaches.

• The Journal of the Acoustical Society of Korea
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• v.21 no.8
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• pp.719-726
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• 2002

In this paper, we present a layered watermarking technique for digital audio data that is capable of detecting timing change and adapting complexity in detection. The proposed watermarking uses echo hiding as the first layer, which enables the detector to estimate linear speed change. The spread spectrum watermark is then inserted in the second layer which includes additional information like copyright data. We use two kinds of sequences in the second layer, one of which is for synchronization and the other is for data. The results of previous layer are used to make estimate of timing change in the next layer. The detector in the presented method can select detecting range form the first layer to the first layer, second pre-layer, or second main-layer due to the required system specification. Experimental results show that the proposed watermarking technique is robust to several processing attacks including timing change.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1259-1266
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• 2014

Road signs provide important safety information about road and traffic conditions to drivers. Road signs include not only common traffic signs but also warning information regarding unexpected obstacles and road constructions. Therefore, accurate detection and identification of road signs is one of the most important research topics related to safe driving. In this paper, we propose a 3-D vision technique to automatically detect and track road signs in a video sequence which is acquired from a stereo vision camera mounted on a vehicle. First, color information is used to initially detect the sign candidates. Second, the SVM (Support Vector Machine) is employed to determine true signs from the candidates. Once a road sign is detected in a video frame, it is continuously tracked from the next frame until it is disappeared. The 2-D position of a detected sign in the next frame is predicted by the 3-D motion of the vehicle. Here, the 3-D vehicle motion is acquired by using the 3-D pose information of the detected sign. Finally, the predicted 2-D position is corrected by template-matching of the scaled template of the detected sign within a window area around the predicted position. Experimental results show that the proposed method can detect and track many types of road signs successfully. Tracking comparisons with two different methods are shown.

• Food Science of Animal Resources
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• v.29 no.5
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• pp.647-652
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• 2009

A duplex PCR technique was applied for specific identification of cow and goat milk in milk products by using primers targeting the mitochondrial 12S rRNA gene. Duplex PCR using primers specific for cow and goat generated specific fragments of 223bp and 326bp from cow and goat milk DNA, respectively. Duplex PCR was applied to 15 milk products purchased from the market to verify label statements. The labeling statements of four market milk products, three yoghurt products, and one whole milk powder product were confirmed in the duplex PCR. The labeling statements of five of seven infant milk powder products were also confirmed by duplex PCR but the other two products were shown to be contaminated with either cow or goat milk. The proposed duplex PCR provides a rapid and sensitive approach to detection of as little as 0.1% cow milk in goat milk and one-step detection of cow or goat milk in milk products.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.5
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• pp.466-472
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• 2009

An acoustic leak monitoring system(ALMS) using acoustic emission(AE) technique was applied for leakage detection of nuclear power plant's pipeline which is operated in high temperature and pressure condition. Since this system only monitors the existence of leak using the root mean square(RMS) value of raw signal from AE sensor, the difficulty occurs when the characteristics of leak size and shape need to be evaluated. In this study, dual monitoring system using AE sensor and accelerometer was introduced in order to solve this problem. In addition, artificial neural network(ANN) with Levenberg.Marquardt(LM) training algorithm was also applied due to rapid training rate and gave the reliable classification performance. The input parameters of this ANN were extracted from varying signal received from experimental conditions such as the fluid pressure inside pipe, the shape and size of the leak area. Additional experiments were also carried out and with different objective which is to study the generation and characteristic of lamb and surface wave according to the pipe thickness.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.2
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• pp.144-149
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• 2011

The lock-in thermography was employed to evaluate the integrity of railway bogies. Prior to the actual application on railway bogies, in order to assess the detectability of known flaws, the calibration reference panel was prepared with various dimensions of artificial flaws. The panel was composed of structural steel, which was the same material with actual bogies. Through lock-in thermography evaluation, the optimal frequency of heat source was determined for the best flaw detection. Based on the defects information, the actual defect assessments on railway bogie were conducted with different types of railway bogies, which were used for the current operation. In summary, the defect assessment results with thermography method showed a good agreement as compared with the conventional inspection techniques. Moreover, it was found that the novel infrared thermography technique could be an effective way for the inspection and the detection of surface defects on bogies since the infrared thermography method provided rapid and non-contact mode for the investigation of railway bogies.

• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.219-228
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• 2009

The growing application and the numerous qualities of induction motors (1M) in industrial processes that require high security and reliability levels has led to the development of multiple methods for early fault detection. However, various faults can occur, such as stator short-circuits and rotor failures. Traditionally the diagnosis machine is done through a sinusoidal power supply, in the present paper we study experimentally the effects of the rotor failures, such as broken rotor bars in function of the ac supplying, the load and show the impact of the converter from diagnosis of the machine. The technique diagnosis used is based on the spectral analysis of stator currents or stator voltages respectively according to the types of induction motor ac supplying. So, four different ac supplying are considered: ${\odot}$ the IM is directly by the balanced three-phase network voltage source, ${\odot}$ the IM is fed by a sinusoidal current source given the controlled by hysteresis, ${\odot}$ the IM is fed (in open loop) by a scalar control imposing through ratio V/f=constant, ${\odot}$ the IM is controlled through a vector control using space vector pulse width modulation (SVPWM) technique inverter with an outer speed loop.