• Journal of Korea Multimedia Society
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• v.14 no.12
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• pp.1544-1548
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• 2011

A process of choosing a subset of original features, so called feature selection, is considered as a crucial preprocessing step to image processing applications. There are already large pools of techniques developed for machine learning and data mining fields. In this paper, basically two methods, non-feature selection and feature selection, are investigated to compare their predictive effectiveness of classification. Color co-occurrence feature is used for defining image features. Standard Sequential Forward Selection algorithm are used for feature selection to identify relevant features and redundancy among relevant features. Four color spaces, RGB, YCbCr, HSV, and Gaussian space are considered for computing color co-occurrence features. Gray-level image feature is also considered for the performance comparison reasons. The experimental results are presented.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.137-140
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• 2008

Recently many areas require wide field of view images. Such as surveillance, virtual reality, navigation and 3D scene reconstruction. Conventional camera systems have a limited filed of view and provide partial information about the scene. however, omni directional vision system can overcome these disadvantages. Acquiring 360 degree panorama images requires expensive omni camera lens. In this study, 360 degree panorama image was tested using a low cost optical reflector which captures 360 degree panoramic views with single shot. This 360 degree panorama image system can be used with detailed positional information from GPS/INS. Through this study result, we show 360 degree panorama image is very effective tool for mobile monitoring system.

• Journal of the Korean Society of Costume
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• v.60 no.1
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• pp.28-42
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• 2010

A purpose of this study is to 6nd out how the casual and formal style clothes of stripe pattern giving variety by pattern direction, pattern width, and contrast coloration have an effect on image of wearers. For this, 192 stimuli were made and 1200 testee evaluated them using semantic differential scale. As a result, five image dimensions were drawn as a factor of attractiveness, gracefulness, activeness, visibility, and tenderness. Unlike the value contrast previously researched, it showed that chroma contrast coloration which was interacted with a color tone contrast coloration had an effect on all the 5 image dimensions. This result was recognized as significant clothes dues in evaluating the image of stripe wearers. Besides, clothing style, stripe pattern, and contrast coloration were made clear as an efficient parameter in image presentation of clothing wearers.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1437-1446
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• 2020

For the last few years, smart devices have begun to occupy an essential place in the life of children, by allowing them to access a variety of language activities and books. Various studies are being conducted on using smart devices for education. Our study extracts images and texts from kids' book with smart devices and matches the extracted images and texts to create new images that are not represented in these books. The proposed system will enable the use of smart devices as educational media for children. A deep convolutional generative adversarial network (DCGAN) is used for generating a new image. Three steps are involved in training DCGAN. Firstly, images with 11 titles and 1,164 images on ImageNet are learned. Secondly, Tesseract, an optical character recognition engine, is used to extract images and text from kids' book and classify the text using a morpheme analyzer. Thirdly, the classified word class is matched with the latent vector of the image. The learned DCGAN creates an image associated with the text.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.633-640
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• 2022

As service robots are applied to various fields, interest in an image processing processor that can perform an image processing algorithm quickly and accurately suitable for each task is increasing. This paper introduces an image processing processor design method applicable to robots. The proposed processor consists of an AGX board, FPGA board, LiDAR-Vision board, and Backplane board. It enables the operation of CPU, GPU, and FPGA. The proposed method is verified through simulation experiments.

• Journal of Multimedia Information System
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• v.6 no.4
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• pp.203-208
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• 2019

Fast operation of a CNN based object detection is important in many application areas. It is an efficient approach to reduce the size of an input image. However, it is difficult to find an area that includes a target object with minimal computation. This paper proposes a ROI detection method that is fast and robust to noise. The proposed method is not affected by a flicker line noise that is a kind of aliasing between camera and LED light. Fast operation is achieved by using down-sampling efficiently. The accuracy of the proposed ROI detection method is 92.5% and the operation time for a frame with a resolution of 640 × 360 is 0.388msec.

• Proceedings of the IEEK Conference
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• summer
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• pp.82-85
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• 2004

This paper proposes an advanced circuit for the capacitive type fingerprint sensor signal processing and an effective isolation structure for minimizing an electrostatic discharge(ESD) influence and for removing a signal coupling noise of each sensor pixel. The proposed detection circuit increases the voltage difference between a ridge and valley about $80\%$ more than old circuit. The test chip is composed of $160\;\times\;192$ array sensing cells $(9,913\times11,666\;um^2).$ The sensor plate area is $58\;\times\;58\;um^2$ and the pitch is 60um. The image resolution is 423 dpi. The chip was fabricated on a 0.35um standard CMOS process. It successfully captured a high-quality fingerprint image and performed the registration and identification processing. The sensing and authentication time is 1 sec(.) with the average power consumption of 10 mW at 3.0V. The reveal ESD tolerance is obtained at the value of 4.5 kV.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.4
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• pp.93-100
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• 2005

In this paper, we describe biometric watermarking techniques for secure user verification on the remote, multimodal biometric system employing both fingerprint and face information, and compare their effects on verification accuracy quantitatively. To hide biometric data with watermarking techniques, we first consider possible two scenarios. In the scenario 1, we use a fingerprint image as a cover work and hide facial features into it. On the contrary, we hide fingerprint features into a facial image in the Scenario 2. Based on the experimental results, we confirm that the Scenario 2 is superior to the Scenario 1 in terms of the verification accuracy of the watermarking image.

• Journal of Astronomy and Space Sciences
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• v.32 no.2
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• pp.113-120
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• 2015

When humans explore the Moon, lunar caves will be an ideal base to provide a shelter from the hazards of radiation, meteorite impact, and extreme diurnal temperature differences. In order to ascertain the existence of caves on the Moon, it is best to visit the Moon in person. The Google Lunar X Prize(GLXP) competition started recently to attempt lunar exploration missions. Ones of those groups competing, plan to land on a pit of Lacus Mortis and determine the existence of a cave inside this pit. In this pit, there is a ramp from the entrance down to the inside of the pit, which enables a rover to approach the inner region of the pit. In this study, under the assumption of the existence of a cave in this pit, a 3D model was developed based on the optical image data. Since this model simulates the actual terrain, the rendering of the model agrees well with the image data. Furthermore, the 3D printing of this model will enable more rigorous investigations and also could be used to publicize lunar exploration missions with ease.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.3
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• pp.97-102
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• 2008

In this paper we propose an object-based image retrieval method using spatial color model and feature points registration method for an effective color query detection. The proposed method in other to overcome disadvantages of existing color histogram methods and then this method is use the HMMD model and rough set in order to segment and detect the wanted image parts as a real time without the user's manufacturing in the database image and query image. Here, we select candidate regions in the similarity between the query image and database image. And we use SIFT registration methods in the selected region for object retrieving. The experimental results show that the proposed method is more satisfactory detection radio than conventional method.