• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.1
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• pp.210-216
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• 2014

The edge in the image is a part which the brightness changes rapidly between the object and the object or objects and background, and includes information of the features such as size, position, orientation, and texture of the object. The edge detection is the technique that acquires these information of the images, and now the researches to detect edges are making steady progress. Typical conventional edge detection methods are Sobel, Prewitt, Roberts using the first derivative operator and Laplacian method using the second derivative operator and so on. These methods is more or less insufficient that the characteristics of the edge detection in the image added salt and pepper noise. therefore, in this paper, an edge detection algorithm using modified mask that applies different size mask according to noise density of local mask is proposed.

• Journal of IKEEE
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• v.13 no.2
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• pp.232-240
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• 2009

This paper presents a robust vehicle detection and tracking algorithm for supervision of illegal parking. The proposed algorithm is composed of four parts. First, a vehicle detection algorithm is proposed using the improved codebook object detection algorithm to segment moving vehicles from the input sequence. Second, a preprocessing technique using the geometric characteristics of vehicles is employed to exclude non-vehicle objects. Then, the detected vehicles are tracked by an object tracker which incorporates histogram tracking method with Kalman filter. To make the tracking results more accurate, histogram tracking results are used as measurement data for Kalman filter. Finally, Real Stop Counter (RSC) is introduced for trustworthy and accurate performance of the stopped vehicle detection. Experimental results show that the proposed algorithm can track multiple vehicles simultaneously and detect stopped vehicles successfully in the complicated street environment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.6
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• pp.1525-1540
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• 2015

Due to a rapid advancement in the electronic commerce technology, the payment method varies from cash to electronic settlement such as credit card, mobile payment and mobile application card. Therefore, financial fraud is increasing notably for a purpose of personal gain. In response, financial companies are building the FDS (Fraud Detection System) to protect consumers from fraudulent transactions. The one of the goals of FDS is identifying the fraudulent transaction with high accuracy by analyzing transaction data and personal information in real-time. Data mining techniques are providing great aid in financial accounting fraud detection, so it have been applied most extensively to provide primary solutions to the problems. In this paper, we try to provide an overview of the research on data mining based fraud detection. Also, we classify researches under few criteria such as data set, data mining algorithm and viewpoint of research.

• Journal of Satellite, Information and Communications
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• v.12 no.4
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• pp.141-145
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• 2017

Spectrum sensing is a critical functionality of Cognitive Radio(CR) systems and the CR systems can be applied to RF energy harvesting systems to improve an energy harvesting rate. There are number of spectrum sensing techniques. One of techniques is energy detection. Energy detection is the simplest detection method and is the most commonly used. But, energy detection has a hidden terminal problem in real wireless communication, because of secondary user (SU) can be affected by frequency fading and shadowing. Cooperative spectrum sensing can solve this problem using spatial diversity of SUs. But it has a problem of increasing data by processing multiple secondary. So, we propose the system model using adaptive spectrum sensing algorithm and system model is simulated. This algorithm chooses sensing method between single energy sensing and cooperative energy according to the received signal's Signal to Noise Ratio (SNR) from Primary User (PU). The simulation result shows that adaptive spectrum sensing has an efficiency and improvement in CR systems.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.35-44
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• 2010

In this paper, we propose a method about producing skin color model adaptively in input image and face detection. The principle process which we proposed is finding eyes candidates by applying the eye features to neural network, and then using the around color to find the distribution of color value. There will be a verification process that producing face region by using color value distribution which is detected as skin region and find mouth candidate in corresponding face region; if eye candidate and mouth candidate's connection structure is similar with face structure, then it can be judged as a face. Because this method can detect skin region adaptively by finding eyes, we solve the rate of false positive about the distorted skin color which is used by existing face detection methods. The experiment was performed about detecting the eye, the skin, the mouth and the face individually. The results revealed that the proposed technique is better than the traditional techniques.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.1
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• pp.75-80
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• 2013

Background: Breast cancer is the most common cancer diagnosed in females in Sri Lanka and early detection can lead to reduction in morbidity and mortality. Aim: To evaluate selected aspects of breast cancer early detection services implemented through well woman clinics (WWCs) in the Gampaha District. Methods: The study consisted of two components. A retrospective descriptive arm assessed clinical breast examination (CBE) coverage of target age group women (TGW) of 35-59 years in all the WWCs in Gampaha district over 2003-2007. A cross sectional descriptive study additionally assessed quality of breast cancer early detection services. The Lot Quality Assurance Sampling (LQAS) technique was used to decide on the lot size and threshold values, which were computed as twenty and six clinics. Checklists were employed in assessing coverage, physical facilities and clinic activities. Client satisfaction on WWC services was assessed among 200 TGW attending 20 WWCs using an interviewer-administered questionnaire. Results: CBE coverage in the Gampaha district increased only from 1.1-2.2% over 2003-2007. With regard to physical facilities, the number of clinics that were rated substandard varied between 7-18 (35-90%). The items that were lacking included dust bins, notice boards, stationary, furniture and linen, and cleanliness of outside premises and toilets. With regard to clinic activities, punctuality of staff, late commencement of clinics, provision of health education, supervision, CBE and breast self-examination (BSE) were substandard in 7-20 clinics (35-100%). Client satisfaction for WWC services was 45.2% (IQR: 38.7-54.8%) and only 11% had a score of ${\geq}70%$, the cut off set for satisfaction. Conclusions: Breast cancer early detection service coverage in the Gampaha district remained low (2.2%) in 2007, 11 years after commencing WWCs. All 20 clinics were substandard for overall CBE and BSE.

• Journal of Broadcast Engineering
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• v.25 no.3
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• pp.362-373
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• 2020

Recently, as autonomous vehicles and intelligent CCTV are growing more interest, the efficient object detection is essential technique. The DPM(Deformable Part Models) which is basis of this paper have used a typical object system that represents highly variable objects using mixtures of deformable part for object. Although it shows high detection performance by capturing part shape and configuration of object model, but it is limited to use in real application due to the complicated algorithm. In this paper, instead of image feature pyramid that takes up a large amount of computation in one part of the detector, we propose a method to reduce the computation speed by reconstructing a new image feature pyramid that uses adaptive bilinear interpolation of feature maps obtained on a specific image scale. As a result, the detection performance for object was lowered a little by 2.82%, however, the proposed detection method improved the speed performance by 10% in comparison with original DPM.

• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.4
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• pp.369-375
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• 2012

In order to overcome the detection limit by the current nondestructive evaluation technology, a nonlinear resonant ultrasound spectroscopy(NRUS) technique was applied for detection of micro-scale cracks in a material. A down-shift of the resonance frequency and a variation of normalized amplitude of the resonance pattern were suggested as the nonlinear parameter for detection of micro-scale cracks in a materials. A natural-like crack were produced in a standard compact tension(CT) specimen by a low cycle fatigue test and the resonance patterns were acquired in each fatigue step. As the exciting voltage increases, a down-shift of resonance frequency were increases as well as the normalized amplitude decrease. This nonlinear effects were significant and even greater in the cracked specimen, but not observed in a intact specimen.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.9
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• pp.89-95
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• 2015

In this paper, we propose a real-time two-dimensional bar code detection system even at long range using a vision technique. We first perform short-range detection, and then long-range detection if the short-range detection is not successful. First, edge map generation, image binarization, and connect component labeling (CCL) are performed in order to select a region of interest (ROI). After interpolating the selected ROI using bilinear interpolation, a location symbol pattern is detected as the same as for short-range detection. Finally, the symbol pattern is arranged by applying inverse perspective transformation to localize bar codes. Experimental results demonstrate that the proposed system successfully detects bar codes at two or three times longer distance than existing ones even at indoor environment.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.4
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• pp.59-70
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• 2008

In this paper, we proposed image processing technique for automatic real-time fire and smoke detection in tunnel environment. To avoid the large scale of damage of fire occurred in variety environments, it is purposeful to propose many studies to minimize and to discover the incident as fast as possible. But we need new specific algorithm because tunnel environment is quite different and it is difficult to apply previous fire detection algorithm to tunnel environment. Therefore, in this paper, we proposed specific algorithm which can be applied in tunnel environment. To minimize false detection in tunnel we used color and motion information. And it is possible to detect exact position in early stage with detection, test, verification procedures. In addition, by comparing properties of each algorithm throughout experiment, we have proved the validity and efficiency of proposed algorithm.