• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2006.06a
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• pp.53-56
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• 2006

In this paper, we present the algorithm to enhance the high frequency components of the image by subtracting smoothing version of an image from the original image. In a word, this is the technique to get more a precise and vivid image. The method of Gaussian smoothing is accepted to get the components of the flat image. Moreover we need to consider the size of the gain of the proposed filter in order to preserve the overall brightness of a image. Based on the algorithm verified by MATLAB, we can obtain more vivid and fuller detail of the image than an original image.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.111-115
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• 2020

In this paper, I proposed an effective technique for accurately predicting pixel values using edge components. Adjacent pixel values are similar to each other. That is, generally, similarity exists between adjacent pixels in an image. In the proposed algorithm, edge components are detected using the surrounding pixels in the first step, and pixel values are estimated using the edge components in the second step. Therefore, the prediction accuracy of the pixel value is improved and the prediction error is reduced. Pixel value prediction is a necessary technique for various applications such as image magnification and confidential data concealment. Experimental results show that the proposed method has higher prediction accuracy and fewer prediction error. Therefore, the proposed technique can be effectively used for applications such as image magnification and confidential data concealment.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.6
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• pp.345-351
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• 2014

This paper presents pedestrian recognition to improve performance for vehicle safety system or surveillance system. Pedestrian detection method using HOG (Histograms of Oriented Gradients) has showed 90% recognition rate. But if someone takes a picture in the rain, the image may be distorted by rain streaks and recognition rate goes down by 62%. To solve this problem, we applied image decomposition method using MCA (Morphological Component Analysis). In this case, rain removal method improves recognition rate from 62% to 70%. However, it is difficult to apply conventional image decomposition method using MCA on vehicle safety system or surveillance system as conventional method is too slow for real-time system. To alleviate this issue, we propose a rain removal method by using low-pass filter and DCT (Discrete Cosine Transform). The DCT helps separate the image into rain components. The image is removed rain components by Butterworth filtering. Experimental results show that our method achieved 90% of recognition rate. In addition, the proposed method had accelerated processing time to 17.8ms which is acceptable for real-time system.

• Journal of Korea Multimedia Society
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• v.22 no.1
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• pp.35-43
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• 2019

Template tracking refers to the procedure of finding the most similar image patch corresponding to the given template through an image sequence. In order to obtain more accurate trajectory of the template, the template requires to be updated to reflect various appearance changes as it traverses through an image sequence. To do that, appearance images are used to model appearance variations and these are obtained by the computation of the principal components of the augmented image matrix at every iteration. Unfortunately, it is prohibitively expensive to compute the principal components at every iteration. Thus in this paper, we suggest a new Sliding Window based truncated URV Decomposition (TURVD) algorithm which enables updating their structure by recycling their previous decomposition instead of decomposing the image matrix from the beginning. Specifically, we show an efficient algorithm for updating and downdating the TURVD simultaneously, followed by the rank-one update to the TURVD while tracking the decomposition error accurately and adjusting the truncation level adaptively. Experiments show that the proposed algorithm produces no-meaningful differences but much faster execution speed compared to the typical algorithms in template tracking applications, thereby maintaining a good approximation for the principal components.

• Journal of Fashion Business
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• v.22 no.4
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• pp.160-177
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• 2018

The objective of this study was to investigate mediation effect of appearance management behavior on the relationship between satisfaction of personal image and job search efficacy. Based on previous studies on components of personal image, appearance management behaviors, and job search efficacy, questionnaire items were developed. For this study, we conducted a questionnaire survey among 422 students from women's university in Seoul. Statistical analyses were performed using SPSS 23. Results are as follows. First, there were positive and moderate bivariate correlations among satisfaction of personal image, appearance management behavior, and job search efficacy. Second, satisfaction of personal image was found to have a partially significant effect on job search efficacy while satisfaction of internal image, visual image, and social image had a positive effect on job search skill. Satisfaction of internal image had a positive effect on job search strength. However, satisfaction of visual image or social image did not have a significant effect on job search strength. Third, fashion management behavior among components appearance management behavior could partially mediate the relationship between satisfaction of personal image and job search efficacy, indicating that satisfaction of internal image and visual image among components personal image not only has a direct effect on job search skill among job search efficacy, but also has an indirect effect on job search skill by affecting fashion management behavior. These results suggest that it is important to build personal image effectively and increase satisfaction with oneself through active appearance management behavior to improve job search efficacy.

• Journal of Korea Multimedia Society
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• v.7 no.3
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• pp.349-356
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• 2004

In this paper, a practical image security system using SA algorithm and 4-f optical correlator system is proposed. The encrypted image and key image with binary phase components are generated using an iterative SA algorithm. a decrypted image is found through the correlation of the encrypted and key images using 4-f optical correlator system. The encrypted and key images are consisted of binary phase components. So, it is easy to implement the optical security system using the proposed technique. And if we fix the encrypted image in the optical security system and change the key images, we get different images, so it is possible to apply to the distinguished authorization system using different key images. Computer simulations show that despite the binary phase components of the two images(encrypted and key image), decrypted images are generated.

• Journal of the Optical Society of Korea
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• v.15 no.2
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• pp.140-145
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• 2011

Joint transform correlator (JTC) is a well known tool for color pattern recognition for a color image. Color images have red, green and blue components, thus in conventional JTC, three input channels of these color components are necessary for color pattern recognition. This paper proposes a new technique of color pattern recognition by decomposing the color image into three color components and recombining those components into a single gray image in the input plane. This new technique needs single input channel and single output CCD camera, thus a simple JTC can be used. We present various kinds of simulated results to show that our newly proposed technique can accurately recognize and discriminate color differences.

• Korean Journal of Human Ecology
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• v.18 no.1
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• pp.247-257
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• 2009

The purpose of this study was to examine the effects of interior color and product volume of clothing shop on consumer's store image and preference for a clothing shop. The research methodology was a survey questionnaire and the subjects were 516 university students in Daejeon, Korea. The measuring instruments were stimuli and self-administrated questionnaire. The stimuli were 7 pictures of clothing shop including interior color and product volume variables, and the self-administrated questionnaire consisted of semantic differential scales for store image, store preference, and subject's demographic attribution. The data were analyzed by t-test, ANOVA, MANOVA, Duncan's multiple range test, based on SPSS program The results were as follows: first, in clothing shop's interior colors affecting store image and preference for clothing shop, white color gave a casual, sophisticated, characteristic, and attractive image to the shops, and brown color gave an elegant, sophisticated image, while black color gave a sophisticated, uncomfortable image, and gray color gave a less positive image to them than other colors. Subjects preferred white, brown, and black color in the order. Second, clothing shop's products volume also affected consumers' store image and preference. Its small volume gave a more sophisticated, elegant image than other volume levels, and subjects preferred small and medium volume of clothing products to their large volume. Third, the effects of shop's interior color and clothes' product volume on store image were different depending on subject's sex. The results revealed that clothing shop's interior color and product volume are important VMD components affecting consumer's store image and preference, and consumer's sex has to be considered to understand the effects of VMD components on clothing shop image.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.747-750
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• 2001

The paper presents an algorithm for estimating the variance of additive zero mean Gaussian noise in an image. The algorithm uses the wavelet transform which is a good tool for energy compaction. The algorithm consists of three steps. At first, high frequency components, wavelet coefficients in HH band, are generated from a noisy image by the wavelet transform. In a second step, high frequency components which are out of the noise range ate eliminated. Finally, if the image has many components eliminated in the previous step, then its noise estimated value is reduced. Experimental results show that the wavelet filter has better performance than the other high pass filters such as a Laplacian filter, residual from a median filter, residual from a mean filter, and a difference operator. In various images, the algorithm reduces 50% of estimated error on an average.

• Journal of the Semiconductor & Display Technology
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• v.11 no.3
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• pp.39-44
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• 2012

Electronics in modern lives have become more miniaturized and precise. Multi Layered Ceramic Capacitor (MLCC) occupies 50% of electronic components consisting of electronics. This high volume of the production needs high speed and more precise machine performances. The dominate parts of the production equipments are the module transporting components and the visual inspection module. Most visual inspection has been off-line because of the image processing time. In this paper, a new image processing method is proposed to reduce thousands of matrix calculation for image processing and realize on-line high speed inspection.