• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.2
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• pp.152-157
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• 2010

The development of computer and internet has introduced various types of media - such as, image, audio, video, and voice - to the traditional text-based information. However, most of the information retrieval systems are based only on text, which results in the absence of ability to use available information. By utilizing the available media, one can improve the performance of search system, which is commonly called content-based retrieval and content-based image retrieval system specifically tries to incorporate the analysis of images into search systems. In this paper, a content-based image retrieval system using HSI color space, ART2 algorithm, and SOM algorithm is introduced. First, images are analyzed in the HSI color space to generate several sets of features describing the images and an SOM algorithm is used to provide candidates of training features to a user. The features that are selected by a user are fed to the training part of a search system, which uses an ART2 algorithm. The proposed system can handle the case in which an image belongs to several groups and showed better performance than other systems.

• Korean Journal of Construction Engineering and Management
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• v.17 no.5
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• pp.62-70
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• 2016

Construction engineers are the core resource for the sustainable development of construction industry and positive images toward construction engineers give much impacts on recruit and retainment of the young and talented. Although previous studies reported on negative aspects of the image of construction industry, the image of construction engineers has not been properly investigated to date. The objective of the study is to compare images of construction engineers as perceived by general public and construction engineers themselves in order to identify key characteristics and implications. The result shows that construction engineers themselves, compared with general public, have more negative tendencies on images of construction engineers. The study suggests that it is critical to enhance the understanding of roles of construction engineers and their morality in order to improve general public's perception on construction engineers images. On the other hand, fundamental measures to be taken to restore the environments of construction industry for construction engineers to improve their self-perception on images of construction engineers.

• Journal of the Korean Geotechnical Society
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• v.27 no.11
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• pp.93-101
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• 2011

High quality X-ray computed microtomography (micro-CT) imaging of internal microstructures and pore space in geomaterials is often hampered by some inherent noises embedded in the images. In this paper, we introduce image calibration techniques for removing the most common noises in X-ray micro-CT, cupping (brightness difference between the periphery and central regions) and ring artifacts (consecutive concentric circles emanating from the origin). The artifacts removal sequentially applies coordinate transformation, normalization, and low-pass filtering in 2D Fourier spectrum to raw CT-images. The applicability and performance of the techniques are showcased by describing extraction of 3D pore structures from micro-CT images of porous basalt using artifacts reductions, binarization, and volume stacking. Comparisions between calibrated and raw images indicate that the artifacts removal allows us to avoid the overestimation of porosity of imaged materials, and proper calibration of the artifacts plays a crucial role in using X-ray CT for geomaterials.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.2
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• pp.69-78
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• 2006

This paper is concerned with analyzing the images of Korean automobiles using, so called, sensory engineering, which adapts the sensory and subjective assessment of human beings in evaluating the quality of product. The methodology of analysis is suggested in this paper according to the following steps. First, 14 pairs of adjectives, which describe the image of object cars in view of the semantic differential method, are derived from consulting with several expert panels. Nextly, factor analysis is performed in order to obtain the axises, by which the images space of the object automobiles are specified, and then the images of the object automobiles are measured by the coordinate of all the object automobiles in the image space. In this paper, a sensory estimation experiment is performed to a panel consisting with In undergraduate students residing in the region of Daegu. From the result of analysis of this paper, target images, which the automobile manufacturers are intended, are achieved by and large except one company.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3666-3671
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• 2012

We evaluate the face detection and recognition of depth image that is obtained by infrared range sensor. and Face recognition was usually focused on accuracy aspect but it is not enough to evaluate the performance in testing for real world application. In this paper, we evaluate the overall performance like accuracy, training, test speed and memory use for the well known face recognition algorithm like PCA, LDA, ICA and SVM. This experiment evaluate the good results of depth and colored depth image compatible with the colored image although the file size of depth and colored depth image is 30%~40% less than the colored image. Whereas, LDA got the good accuracy performance next to the SVM and also shows the good performance in speed and the amount of memory.

• Journal of the Korea Convergence Society
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• v.10 no.2
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• pp.255-260
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• 2019

Recently realistic descriptions have been frequently used in anti-smoking campaigns. The same trend can also be seen with regard to posters as a medium of visual communication. It was intended to examine how different types of visual images in anti-smoking campaign posters produced and distributed by the WHO can improve the effectiveness of health communication. This article aims to determine how each of abstract/stylized illustrations and realistic images might affect the three key variables of the Theory of Planned Behavior, which are Attitudes toward the Behavior, Subjective Norms and Perceived Behavioral Control, in relation to quitting smoking. Results showed that realistic images are different in improving the attitudes toward the behavior and subjective norms. However, there are no significant difference between abstract/stylized illustrations and realistic images in Perceived Behavioral Control. The findings of this study suggest that the above-mentioned types of visual information achieve different levels of effectiveness in health communication. It is desirable that more effort be devoted to the interdisciplinary study across the areas of visual design and social psychology, for example, with a view to developing better health communication strategies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.84-89
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• 2019

JPEG is a most widely used standard image compression technology. This research introduces the JPEG image compression algorithm and describes each step in the compression and decompression. Image compression is the application of data compression on digital images. The DCT (discrete cosine transform) is a technique for converting a time domain to a frequency domain. First, the image is divided into 8 by 8 pixel blocks. Second, working from top to bottom left to right, the DCT is applied to each block. Third, each block is compressed through quantization. Fourth, the matrix of compressed blocks that make up the image is stored in a greatly reduced amount of space. Finally if desired, the image is reconstructed through decompression, a process using IDCT (inverse discrete cosine transform). The purpose of this research is to review all the processes of image compression / decompression using the discrete cosine transform method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.213-215
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• 2022

Recently, deep learning technology that processes images has been widely used in fire detection, autonomous driving, and defective product detection. In particular, in order to determine whether a product is contaminated or not, it can be identified through the contaminants passed from the existing sensor data, but technologies for recognizing cracks in products or contaminants themselves as images are being actively studied in various fields. In this paper, a system for classifying uncontaminated normal cups and contaminated cups through images was designed and implemented. The image was analyzed using an open image and a photographed image, and the image was analyzed by extracting the upper part of the cup image using Google Objectron for 3D object recognition. Through this study, it is thought that it will be used in various ways for research that can extract the contamination level of products required in the hygiene field based on images.

• Journal of the Korea Computer Graphics Society
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• v.30 no.2
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• pp.11-19
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• 2024

Demand for small biomimetic robots that can carry out reconnaissance missions without being exposed to the enemy in underground spaces and narrow passages is increasing in order to increase the fighting power and survivability of soldiers in wartime situations. A small compound eye image sensor for environmental recognition has advantages such as small size, low aberration, wide angle of view, depth estimation, and HDR that can be used in various ways in the field of vision. However, due to the small lens size, the resolution is low, and the problem of resolution in the fused image obtained from the actual compound eye image occurs. This paper proposes a compound eye image quality enhancement algorithm based on Image Enhancement and ESRGAN to overcome the problem of low resolution. If the proposed algorithm is applied to compound eye image fusion images, image resolution and image quality can be improved, so it is expected that performance improvement results can be obtained in various studies using compound eye cameras.

• Journal of IKEEE
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• v.19 no.2
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• pp.193-200
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• 2015

In this paper, we propose the radiation measuring algorithm and the device composition using CMOS image sensor. The radiation measuring algorithm using CMOS image sensor is based on the radiation particle distinguishing algorithm projected to the CMOS image sensor and accumulated and average number of pixels of the radiation particles projected to dozens of images per second with CMOS image sensor. The radiation particle distinguishing algorithm projected to the CMOS image sensor measures the radiation particle images by dividing them into R, G and B and adjusting the threshold value that distinguishes light intensity and background from the particle of each image. The radiation measuring algorithm measures radiation with accumulated and average number of radiation particles projected to dozens of images per second with CMOS image sensor according to the preset cycle. The hardware devices to verify the suggested algorithm consists of CMOS image sensor and image signal processor part, control part, power circuit part and display part. The test result of radiation measurement using the suggested CMOS image sensor is as follows. First, using the low-cost CMOS image sensor to measure radiation particles generated similar characteristics to that from measurement with expensive GM Tube. Second, using the low-cost CMOS image sensor to measure radiation presented largely similar characteristics to the linear characteristics of expensive GM Tube.