• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.187-190
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• 2003

Due to complexity of diverse features in urban area, accurate feature extraction is laborious task in aerial and satellite imagery. Especially occlusion by buildings, and image distortion of shadow effects make processing more difficult work. In this study, algorithm was presented to correct of shadow effects in aerial color images. This algorithm enables user to accurately interpretate urban information by correction of shadow effects in aerial color images

• Asia pacific journal of information systems
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• v.33 no.3
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• pp.603-623
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• 2023

While prior work has conducted individuals' password security behavior, there is a relatively neglect to examine individuals' affect and feelings of password fatigue in password change context. Therefore, this study explicated individuals' affective response to the feelings of password fatigue by drawing on several theoretical lens. Survey data collected from 267 users were used to test the model using partial least square analysis. This study found that feelings of password fatigue positively affected the negative password fatigue-induced affect, and also both the feelings of password fatigue and the negative password fatigue-induced affect were negatively related to attitude toward changing passwords, which in turn, leads to the intention to change passwords. Furthermore, this study found that shadow work recognition negatively moderated the relationship between attitude and behavioral intention. This study could offer a new theoretical perspective to understand an individual's security behavior and provide empirical evidences for practitioners in charge of IT security in organizations.

• Journal of the Korea Society of Computer and Information
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• v.15 no.9
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• pp.57-65
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• 2010

This paper describes the method of efficient container number recognition in colored container image with number plate at ATC(Automatic Transfer Crane) in container terminal yard. At the Sinseondae terminal gate in Busan, the container number recognition system is installed by "intelligent port-logistics system technology development", that is government research and development project. It is the method that it sets up the tunnel structure inside camera on the gate and it recognizes the container number in order to recognize the export container cargo automatically. However, as the automation equipment is introduced to the container terminal and the unmanned of a task is gradually accomplished, the container number recognition system for the confirmation of the object of work is required at ATC in container terminal yard. Therefore, the container number recognition system fitted for it is necessary for ATC in container terminal yard in which there are many intrusive of the character recognition through image including a sunlight, rain, snow, shadow, and etc. unlike the gate. In this paper, hardware components of the camera, illumination, and sensor lamp were altered and software elements of an algorithm were changed. that is, the difference of the brightness of the surrounding environment, and etc. were regulated for recognize a container number. Through this, a shadow problem, and etc. that it is thickly below hung with the sunlight or the cargo equipment were solved and the recognition time was shortened and the recognition rate was raised.

• Journal of Electrical Engineering and Technology
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• v.7 no.1
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• pp.115-123
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• 2012

A video analysis system used to detect events in video streams generally has several processes, including object detection, object trajectories analysis, and recognition of the trajectories by comparison with an a priori trained model. However, these processes do not work well in a complex environment that has many occlusions, mirror effects, and/or shadow effects. We propose a new approach to a context-aware video surveillance system to detect predefined contexts in video streams. The proposed system consists of two modules: a feature extractor and a context recognizer. The feature extractor calculates the moving energy that represents the amount of moving objects in a video stream and the stationary energy that represents the amount of still objects in a video stream. We represent situations and events as motion changes and stationary energy in video streams. The context recognizer determines whether predefined contexts are included in video streams using the extracted moving and stationary energies from a feature extractor. To train each context model and recognize predefined contexts in video streams, we propose and use a new ensemble classifier based on the AdaBoost algorithm, DAdaBoost, which is one of the most famous ensemble classifier algorithms. Our proposed approach is expected to be a robust method in more complex environments that have a mirror effect and/or a shadow effect.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.62-65
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• 2000

In this paper we propose skewed angle detection methods for images that contain text that is not aligned horizontally. In most images text areas are aligned along the horizontal axis, however there are many occasions when the text may be at a skewed angle (denoted by 0 < ${\theta}\;{\leq}\;{\pi}$). In the work described, we adapt the Hough transform, Shadow and Threshold Projection methods to detect the skewed angle of text in an input image using the orthogonal angle view property. The results of this method are a primary text skewed angle, which allows us to rotate the original input image into an image with horizontally aligned text. This utilizes document image processing prior to the recognition stage.