• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2881-2894
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• 2014

In complicated environment, context information plays an important role in image segmentation/labeling. The recently proposed auto-context algorithm is one of the effective context-based methods. However, the standard auto-context approach samples the context locations utilizing a fixed radius sequence, which is sensitive to large scale-change of objects. In this paper, we present a scale invariant auto-context (SIAC) algorithm which is an improved version of the auto-context algorithm. In order to achieve scale-invariance, we try to approximate the optimal scale for the image in an iterative way and adopt the corresponding optimal radius sequence for context location sampling, both in training and testing. In each iteration of the proposed SIAC algorithm, we use the current classification map to estimate the image scale, and the corresponding radius sequence is then used for choosing context locations. The algorithm iteratively updates the classification maps, as well as the image scales, until convergence. We demonstrate the SIAC algorithm on several image segmentation/labeling tasks. The results demonstrate improvement over the standard auto-context algorithm when large scale-change of objects exists.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.1
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• pp.1-6
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• 2018

In this paper, we propose the method to eliminate repetitive processes for key-point detection on multi-scale image space. The proposed method detects key-points from the original image, and select a good key-points using the cluster filters, and create the key-point clusters. And it select reference objects by using direction angles of the key-point clusters, predict the scale of the original image by using the distributed distance ratio. It transform the scale of the reference image, and apply the detection of key-points to the transformed reference image. In the results of the experiment, the proposed method can be found to improve the key-points detection time by 75 % and 71 % compared to SIFT method and scaled ORB method using the multi-scale images.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.10
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• pp.1-13
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• 2011

The aim of this study is to analyze the emotion adjectives for light emitting diode(LED) light colors using a twofold adjective image scales from Kobayashi and I.R.I. A set of psychophysical experiments using category judgment was conducted in an LED light color simulation system, in order to evaluate each emotion scale coordinate for those test light colors in both adjective image scales. In total, 49 test light colors from a combination of 6 color series were assessed by 15 human observers. As a result, Kobayashi adjective image scale clearly expressed to emotion adjectives of 'Dynamic', 'Casual', 'Chic', 'Cool-casual', 'Modern', and 'Natural' for different hues. In contrast, I.R.I adjective image scale expressed only 2 adjectives of 'dynamic' and 'luxurious' for the all hues.

• Journal of the Korean Dietetic Association
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• v.14 no.2
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• pp.186-197
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• 2008

The aim of this study was to measure the brand images of contract foodservice management companies by identifying brand image attributes and then developing a measurement scale to measure the weight of these attributes. The measurement scale was developed by following a 5-stage process that included face-to-face interviews with experts, literature review, questionnaire surveys, verification of scale validity, exploratory factor analysis, and confirmatory factor analysis. A total of 137 items measuring brand image were collected: 37 items from studies of brand image and corporate image, 55 items from studies of contract foodservice management companies and 45 items from the internet and websites of contract foodservice management companies. A survey was then conducted to assess the validity and reliability of the questionnaire items. Ultimately, the 137 items were reduced to 40 items. The calculated Cronbach's alpha for the 40 brand image items was 0.934, demonstrating good internal consistency. Based on exploratory factor analysis (EFA), employee attitude, menu content, corporate image, dining location and ambience, along with 33 subattributes, were identified as brand image attributes. Employee attitude was the most significant attribute influencing brand image. After confirmatory factor analysis (CFA) and a review process, four brand image attributes and 33 subattributes were finalized and incorporated into the scale.

• Nutrition Research and Practice
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• v.2 no.2
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• pp.85-92
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• 2008

The present study was conducted to develop a Multi-dimensional Body Image Scale for Malaysian female adolescents. Data were collected among 328 female adolescents from a secondary school in Kuantan district, state of Pahang, Malaysia by using a self-administered questionnaire and anthropometric measurements. The self-administered questionnaire comprised multiple measures of body image, Eating Attitude Test (EAT-26; Gamer & Garfinkel, 1979) and Rosenberg Self-esteem Inventory (Rosenberg, 1965). The 152 items from selected multiple measures of body image were examined through factor analysis and for internal consistency. Correlations between Multi-dimensional Body Image Scale and body mass index (BMI), risk of eating disorders and self-esteem were assessed for construct validity. A seven factor model of a 62-item Multi-dimensional Body Image Scale for Malaysian female adolescents with construct validity and good internal consistency was developed. The scale encompasses 1) preoccupation with thinness and dieting behavior, 2) appearance and body satisfaction, 3) body importance, 4) muscle increasing behavior, 5) extreme dieting behavior, 6) appearance importance, and 7) perception of size and shape dimensions. Besides, a multidimensional body image composite score was proposed to screen negative body image risk in female adolescents. The result found body image was correlated with BMI, risk of eating disorders and self-esteem in female adolescents. In short, the present study supports a multi-dimensional concept for body image and provides a new insight into its multi-dimensionality in Malaysian female adolescents with preliminary validity and reliability of the scale. The Multi-dimensional Body Image Scale can be used to identify female adolescents who are potentially at risk of developing body image disturbance through future intervention programs.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.4
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• pp.704-722
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• 2022

Current studies validate the Body Positive Scale (BP Scale) as a self-assessment instrument that captures four dimensions of the positive body image construct. We developed and evaluated a 17-item BP Scale using two focus group interviews and four independent samples (n = 1,379) of Korean women who completed online survey questionnaires. We generated an initial pool of items via literature review, content validation with experts, and focus group interviews, subsequently refining the items through exploratory analysis (Study 1). We confirmed the BP Scale's underlying dimensions with young Korean female samples (Study 2, Study 4) and with a community sample (Study 3). We also examined the construct validity, internal consistency, and test-retest reliability over a six-week interval. Overall, the results supported that the four-factor BP Scale demonstrates adequate validity and reliability in measuring positive body image among Korean women. The BP Scale provides a method for researchers and practitioners to understand and assess individuals' positive body image in a multifaceted manner.

• Journal of Korean Academy of Nursing
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• v.15 no.3
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• pp.74-80
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• 1985

This study was attempted to identify the difference between body image of the patients with lower limb fracture and that of normal persons, and to examine if supportive group care could offer an apportunity for positive change in body image of the patient with lower limb fracture under the Quasi-experimental design. The subjects for this study were obtained by ta-king convenient sample of soldiers; the experimental group were 44 lower limb fractured patients hospitalized on the orthopedic Surgery unit in S Army General Hospital, while the control group were 44 normal enlisted men serving in the B Army regiment. Supportive group nursing care was given to the lower limb fractured patients who belong to the experimental group. Pre-and post-tests were administered to the experimental and the control group. The instruments to measure body image of the subjects were body Cathexis Scale developed by Scord and Jourard (1953) and Body Meaning Scale dove-loped by the reseacher. The reliability coefficients by Cronhach's u-test were .95 in body Cathexis Scale and .89 in Body Meaning Scale in this study. Data for this study were collected over a period 12 days from the 12th to the 24th of October, 1984 by the questionnaire. Data were analyzed by computer. Frequency, Percentage and x²-test were used to examine general chacteristics of the subjects. t-test was used to analyze the hypotheses. Analysis of variance was used to test difference in body image between groups classified by the general characteristics. Pearson Correlation Coefficient was used to identify the correlation between Body Cathexis Scale and Body Cathexis Scale and Body Meaning Scale. The results of this study were as follows: 1. No significant difference was found between the experimental and the control group on general characteristics of the subjects (p> .05). 2. Hypothesis I:“There will be a difference in body image between patiens with lower limb fracture and normal persons,”was supported(Body Cathexis t=6.91, p<.001, Body Meaning t=5.66, p< .001). 3. Hypothesis Ⅱ;“The will be a difference in body image of patients with lower limb fracture bet-ween after and before, supportive group nursing care was provided,”was supported (Body Cathexis t=5.90, p<.001, Body Meaning t=4.45, p <.001). 4. There was no significant difference in body image between groups classified by the general characteristics (p> .05). 5. The correlation between Body Cathexis Scale and Body Meaning Scale: It was reported that Body Cathexis Scale correlated with Body Meaning Scale in total subjects of the experimental and control group (r=.744, p<.001). That is, there was relatively high correlation between two scales. body Cathexis Scale correlated with Body Meaning Scale in the experimental group(r=.738, p <.001) and in the control group (r=.352, p <.001). That is, there was more than moderate correlation between two scales. In conclusion, it was found that there was a difference in body image between patients with lower limb fracture and normal persons, and supportive group nursing care offered an opportunity for positive change in body image of the patient with lower limb fracture.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.367-370
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• 2005

This paper proposes a novel method for content-based watermarking based on feature points of an image. At each feature point, watermark is embedded after affine normalization according to the local characteristic scale and orientation. The characteristic scale is the scale at which the normalized scale-space representation of an image attains a maximum value, and the characteristic orientation is the angle of the principal axis of an image. By binding watermarking with the local characteristics of an image, resilience against affine transformations can be obtained. Experimental results show that the proposed method is robust against various image processing steps including affine transformations, cropping, filtering, and JPEG compression.

• Journal of KIISE:Software and Applications
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• v.26 no.1
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• pp.150-150
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• 1999

In this paper, a content-based image retrieval scheme based on scale-space theory is proposed. The existing methods using scale-space theory consider all scales for image retrieval,thereby requiring a lot of computation. To overcome this problem, the proposed algorithm utilizes amodified histogram intersection method to select candidate images from database. The relative scalebetween a query image and a candidate image is calculated by the ratio of histograms. Feature pointsare extracted from the candidates using a corner detection algorithm. The feature vector for eachfeature point is composed of RGB color components and differential invariants. For computing thesimilarity between a query image and a candidate image, the euclidean distance measure is used. Theproposed image retrieval method has been applied to various images and the performance improvementover the existing methods has been verified.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.69-77
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• 2017

This paper represents a novel framework for multi-scale image fusion. Multi-scale Kalman Smoothing (MKS) algorithm with quad-tree structure can provide a powerful multi-resolution image fusion scheme by employing Markov property. In general, such approach provides outstanding image fusion performance in terms of accuracy and efficiency, however, quad-tree based method is often limited to be applied in certain applications due to its stair-like covariance structure, resulting in unrealistic blocky artifacts at the fusion result where finest scale data are void or missed. To mitigate this structural artifact, in this paper, a new scheme of multi-scale fusion framework is proposed. By employing Super Resolution (SR) technique on MKS algorithm, fine resolved measurement is generated and blended through the tree structure such that missed detail information at data missing region in fine scale image is properly inferred and the blocky artifact can be successfully suppressed at fusion result. Simulation results show that the proposed method provides significantly improved fusion results in the senses of both Root Mean Square Error (RMSE) performance and visual improvement over conventional MKS algorithm.