• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.16-22
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• 2012

In this paper, we present spiral pattern which suits for optical simulator to calibrate fisheye lens and compensate geometric distortion. Using spiral pattern, we present calibration without mathematical modeling in advance. Proposed spiral pattern used to input image of optical simulator. Using fisheye lens image, we calibrate a fisheye lens by matching geometrically moved dots to corresponding original dots which leads not to need mathematical modeling. Proposed algorithm calibrates using dot matching which matches spiral pattern image dot to distorted image dot. And this algorithm does not need modeling in advance so it is effective. Proposed algorithm is enabled at processing of pattern recognition which has to get the exact information using fisheye lens for digital zooming. And this makes possible at compensation of geometric distortion and calibration of fisheye lens image applying in various image processing.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.112-122
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• 2009

In this paper, we present a novel space-frequency adaptive image restoration approach using vaguelette-wavelet decomposition (VWD). The proposed algorithm classifies a degraded image into flat and edge regions by using spatial information of the wavelet coefficient. For reducing the noise we perform an adaptive wavelet shrinkage process. At edge region candidates, we adopt entropy approach for estimating the noise and remove it by using relative between sub-bands. After shrinking wavelet coefficients process, we restore the degraded image using the VWD. The proposed algorithm can reduce the noise without affecting the sharpness details. Based on the experimental results, the proposed algorithm efficiently proved to be able to restore the degraded image while preserving details.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1424-1436
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• 2020

Although huge progress has been made in current image segmentation work, there are still no efficient segmentation strategies for tree image which is taken from natural environment and contains complex background. To improve those problems, we propose a method for tree image segmentation combining adaptive mean shifting with image abstraction. Our approach perform better than others because it focuses mainly on the background of image and characteristics of the tree itself. First, we abstract the original tree image using bilateral filtering and image pyramid from multiple perspectives, which can reduce the influence of the background and tree canopy gaps on clustering. Spatial location and gray scale features are obtained by step detection and the insertion rule method, respectively. Bandwidths calculated by spatial location and gray scale features are then used to determine the size of the Gaussian kernel function and in the mean shift clustering. Furthermore, the flood fill method is employed to fill the results of clustering and highlight the region of interest. To prove the effectiveness of tree image abstractions on image clustering, we compared different abstraction levels and achieved the optimal clustering results. For our algorithm, the average segmentation accuracy (SA), over-segmentation rate (OR), and under-segmentation rate (UR) of the crown are 91.21%, 3.54%, and 9.85%, respectively. The average values of the trunk are 92.78%, 8.16%, and 7.93%, respectively. Comparing the results of our method experimentally with other popular tree image segmentation methods, our segmentation method get rid of human interaction and shows higher SA. Meanwhile, this work shows a promising application prospect on visual reconstruction and factors measurement of tree.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.163-177
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• 2024

The fingerprint image quality relies on the clearness of separated ridges by valleys and the uniformity of the separation. The condition of skin still dominate the overall quality of the fingerprint. However, the identification performance of such system is very sensitive to the quality of the captured fingerprint image. Fingerprint image quality analysis and enhancement are useful in improving the performance of fingerprint identification systems. A fuzzy technique is introduced in this paper for both fingerprint image quality analysis and enhancement. First, the quality analysis is performed by extracting four features from a fingerprint image which are the local clarity score (LCS), global clarity score (GCS), ridge_valley thickness ratio (RVTR), and the Global Contrast Factor (GCF). A fuzzy logic technique that uses Mamdani fuzzy rule model is designed. The fuzzy inference system is able to analyse and determinate the fingerprint image type (oily, dry or neutral) based on the extracted feature values and the fuzzy inference rules. The percentages of the test fuzzy inference system for each type is as follow: For dry fingerprint the percentage is 81.33, for oily the percentage is 54.75, and for neutral the percentage is 68.48. Secondly, a fuzzy morphology is applied to enhance the dry and oily fingerprint images. The fuzzy morphology method improves the quality of a fingerprint image, thus improving the performance of the fingerprint identification system significantly. All experimental work which was done for both quality analysis and image enhancement was done using the DB_ITS_2009 database which is a private database collected by the department of electrical engineering, institute of technology Sepuluh Nopember Surabaya, Indonesia. The performance evaluation was done using the Feature Similarity index (FSIM). Where the FSIM is an image quality assessment (IQA) metric, which uses computational models to measure the image quality consistently with subjective evaluations. The new proposed system outperformed the classical system by 900% for the dry fingerprint images and 14% for the oily fingerprint images.

• Korean Journal of Radiology
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• v.23 no.4
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• pp.402-412
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• 2022

Objective: To evaluate the image quality and lesion detectability of lower-dose CT (LDCT) of the abdomen and pelvis obtained using a deep learning image reconstruction (DLIR) algorithm compared with those of standard-dose CT (SDCT) images. Materials and Methods: This retrospective study included 123 patients (mean age ± standard deviation, 63 ± 11 years; male:female, 70:53) who underwent contrast-enhanced abdominopelvic LDCT between May and August 2020 and had prior SDCT obtained using the same CT scanner within a year. LDCT images were reconstructed with hybrid iterative reconstruction (h-IR) and DLIR at medium and high strengths (DLIR-M and DLIR-H), while SDCT images were reconstructed with h-IR. For quantitative image quality analysis, image noise, signal-to-noise ratio, and contrast-to-noise ratio were measured in the liver, muscle, and aorta. Among the three different LDCT reconstruction algorithms, the one showing the smallest difference in quantitative parameters from those of SDCT images was selected for qualitative image quality analysis and lesion detectability evaluation. For qualitative analysis, overall image quality, image noise, image sharpness, image texture, and lesion conspicuity were graded using a 5-point scale by two radiologists. Observer performance in focal liver lesion detection was evaluated by comparing the jackknife free-response receiver operating characteristic figures-of-merit (FOM). Results: LDCT (35.1% dose reduction compared with SDCT) images obtained using DLIR-M showed similar quantitative measures to those of SDCT with h-IR images. All qualitative parameters of LDCT with DLIR-M images but image texture were similar to or significantly better than those of SDCT with h-IR images. The lesion detectability on LDCT with DLIR-M images was not significantly different from that of SDCT with h-IR images (reader-averaged FOM, 0.887 vs. 0.874, respectively; p = 0.581). Conclusion: Overall image quality and detectability of focal liver lesions is preserved in contrast-enhanced abdominopelvic LDCT obtained with DLIR-M relative to those in SDCT with h-IR.

• Journal of radiological science and technology
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• v.40 no.2
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• pp.197-203
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• 2017

The purpose of this study was to measure signal to noise ratio (SNR) according to change of equalization from region of interest (ROI) of heart shadow in chest image. We examined images of chest image of 87 patients in a University-affiliated hospital, Seoul, Korea. Chest images of each patient were calculated by using ImageJ. We have analysis socio-demographical variables, SNR according to images, 95% confidence according to SNR of difference in a mean of SNR. Differences of SNR among change of equalization were tested by SPSS Statistics21 ANOVA test for there was statistical significance 95%(p < 0.05). In SNR results, with the quality of distributions in the order of original chest image, original chest image heart shadow and equalization chest image, equalization chest image heart shadow(p < 0.001). In conclusion, this study would be that quantitative evaluation of heart shadow on chest image can be used as an adjunct to the histogram equalization chest image.

• Journal of Korean Clinical Health Science
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• v.2 no.2
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• pp.90-97
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• 2014

Purpose. The purpose of this study was to investigate the relationship between body image, self-esteem, and family strengths in female university students. Methods. One hundred ninety nine female university students participated in data collection. Data on body image, self-esteem, and family strengths were collected via questionnaire between April 2013 and May 2013. Data analysis was done using PASW 18.0 program and included one-way ANOVA, independent t-test and Pearson correlation coefficients analysis. Results. The mean score of body image was 24.20, self-esteem was 25.30, and family strengths was 83.71. Results showed a positive correlation among body image and self-esteem(r=.19, p<.001), and family strengths(r=.16, p<.001). Conclusion. The results indicate that it is necessary to increase body image, self-esteem, and family strengths among female university students. To ensure resonable body image in female university students, self-esteem, and family strengths should be reinforced.

• Journal of Global Scholars of Marketing Science
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• v.18 no.4
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• pp.307-331
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• 2008

The CEO and the Corporate Image is considered very important in the aspect of marketing. The fact that CEO image itself influences the company or value of the product directly and indirectly has been verified through many cases. Recently, the differentiation of products and services between companies became difficult because the disparity in technique between companies retrenched. As a result, the rate of people who decide to purchase or invest their money based on the corporate image or reputation has been increased. Also in the knowledge society like today, the talented employees are the company's customer and the company's necessity for managing those brains of marketing perspective on how to satisfy and attract the customers is being embossed. The Fashion industry is one of the most value-added industry and in those value-added businesses, the most important factor is the human resources' knowledge power. However the study of the relationships among the CEO image, the corporate image and employment brand value in fashion industry has not been carried out yet. This research considers that dynamic relationship exists among the CEO image, corporate image and employment brand value that affects a company's main goal of pursuing benefits and intends to investigate the relationships of the three concepts. The specific purposes of this study were, 1) to analyze the impact of CEO image on a corporate image, 2) to analyze the impact of corporate image on employment brand value, 3) to analyze the impact of CEO image on employment brand value, 4) to analyze whether corporate image plays a mediating role in the relationship between CEO image and employment brand value or not. A survey design with a structured questionnaire was employed for this research. A convenience sample of 398 subjects was selected from two groups, which are university students majoring in fashion and practitioners working in fashion industry. For the data analysis, descriptive statistic (i.e., frequency, percentage), factor analysis, and multiple regression analysis were used by utilizing SPSS 12.0 for Windows program. The results for this research are as follows, first, the study of the impact of CEO image (i.e., Managerial Competence, Reliability/Leadership, Personal Attractiveness) on corporate image (i.e., Product Image, Corporate Social Responsibility Image, Corporate Cultural Image) brought conclusion that the CEO image generally affected the corporate image in fashion industry. Managerial Competence and Reliability/Leadership affected Product Image, Corporate Social Responsibility Image and Corporate Cultural Image. However, while CEO's Personal Attractiveness affected Product Image and Corporate Social Responsibility Image, it did not affect Corporate Cultural Image. Second, the study of the impact of corporate image on employment brand value brought conclusion that corporate image (i.e., Product Image, Corporate Social Responsibility Image, Corporate Cultural Image) affected employment brand value. Corporate Cultural Image affected employment brand value the most and then the Corporate Social Responsibility Image and Product Image. Third, the study of the impact of CEO image on employment brand value brought conclusion that CEO image (i.e., Managerial Competence, Reliability/Leadership, Personal Attractiveness) affected the employment brand value. CEO's Reliability/Leadership affected the employment brand value the most and then CEO's Personal Attractiveness and CEO's Managerial Competence. Forth, the study examined whether corporate image plays a mediating role in relationship of CEO image and employment brand value and concluded that it does. Corporate image played a full mediating role between CEO's Managerial Competence and employment brand value while it played a partial mediating role between CEO's Reliability/Leadership and CEO's Personal Attractiveness. This study is meaningful in a sense that it examines the relationship among the CEO image, corporate image and employment brand value which has not been carried out yet in fashion industry. It will ultimately contribute to the success of a fashion company by providing useful information of establishing strategies for managing proper the CEO and the corporate image to the fashion company and operating the talented employees.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.663-668
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• 2003

This paper presents a new observation system which is useful to observe the scene of the remote controlled robot vision. This system is composed of a motionless camera and head motion detector with a motion sensor. The motionless camera has a fish eye lens and is for observing a hemisphere space. The head motion detector has a motion sensor is for defining an arbitrary subspace of the hemisphere space from fish eye lens. Thus processing the angular information from the motion sensor appropriately, the direction of face is estimated. However, since the fisheye image is distorted, it is unclear image. The partial domain of a fish eye image is selected by head motion, and this is converted to perspective image. However, since this conversion enlarges the original image spatially and is based on discrete data, crevice is generated in the converted image. To solve this problem, interpolation based on an intensity of the image is performed for the crevice in the converted image (space problem). This paper provides the experimental results of the proposed observation system with the head motion detector and perspective image conversion using the proposed conversion and interpolation methods, and the adequacy and improving point of the proposed techniques are discussed.

• Journal of Korea Multimedia Society
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• v.17 no.7
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• pp.849-857
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• 2014

In this paper, we propose a (2,2)-reversible secret image sharing scheme using histogram shifting and difference expansion. Two techniques are widely used in information hiding. Advantages of them are the low distortion between cover and stego images, and high embedding capacity. In secret image sharing procedure, unlike Shamir's secret sharing, a histogram generate that the difference value between the original image and copy image is computed by difference expansion. And then, the secret image is embedded into original and copy images by using histogram shifting. Lastly, two generated shadow images are distributed to each participant by the dealer. In the experimental results, we measure a capacity of a secret image and a distortion ratio between original image and shadow image. The results show that the embedding capacity and image distortion ratio of the proposed scheme are superior to the previous schemes.