• 농촌지도와개발
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• 제26권4호
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• pp.221-232
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• 2019

The purpose of this paper is empirically to identify the factors influencing local food purchase intention. And this study compares to the difference between local food consumer and hypermarket consumer's attitudes toward local food, food lifestyle, and subjective norm. Data were collected from 319 local food consumer and 179 hypermarket consumer to measure the following; attitude toward local food; subjective norm; perceived behavioral control; food lifestyles; demographic information. Results showed that local food consumers are significant differences on attitudes towards health, environment, and local economy. Results also found that subjective norm and perceived behavioral control are significant differences between local food consumer and hypermarket consumers. It means that consumers who express a strong intention to purchase local food seems to link to the food lifestyles. The study suggests that producers and retailers need to develp campaigns explaining how consuming local food supports local businesses and farmers, which will reinforce personal values associated with local consumption.

• 대한수학회보
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• 제18권2호
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• pp.51-53
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• 1982

• 한국산업정보학회논문지
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• 제22권2호
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• pp.1-13
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• 2017

본 논문에서는 낮은 SNR을 가지는 적외선 영상에서 강인한 소형 표적 검출을 위해 모폴로지 차 연산을 수행하여 표적 후보 영역을 찾고 화소 라벨링을 통해 후보 영역의 위치를 찾는다. 기존의 모폴로지 연산 기반의 표적 검출 방법들은 적외선 영상에 존재하는 클러터에 취약하다는 단점으로 인해 검출 정확도가 낮다. 이러한 문제를 해결하기 위해 본 논문에서는 후보 영역에서 표적과 배경 잡음을 분류하기 위해 Moravec 알고리즘과 LCM(Local Contrast Measure) 알고리즘을 결합함으로써 표적 향상과 배경 잡음 억제를 동시에 달성한다. 또한, 제안하는 알고리즘은 기존에 실시간 표적 검출을 위해 개발되었던 모폴로지 연산과 가우시안 거리 함수를 이용한 표적 검출 방법의 단일 객체에 제한적인 검출 문제를 해결하여 복수 객체를 효율적으로 검출할 수 있다.

• 지능정보연구
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• 제13권4호
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• pp.79-90
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• 2007

영상의 품질을 측정하는 것은 영상처리에서 매우 중요한 문제이다. 지금까지 영상 품질을 측정하기 위한 다양한 방법들이 제시되었고, 이들은 수학적인 관점에서 영상의 품질을 적절히 표현해주고 있다. 그러나, 수학적인 측정과 인간의 시각에 의해서 측정되는 품질은 서로 다를 수 있고 영상이 전달되는 최종 대상체는 인간의 시각이기 때문에 이를 고려한 영상품질 측정 방법이 필요하다. 본 논문에서는 사람의 시각적 특성을 고려하여 영상 품질을 측정할 수 있는 통계적 방법을 제시하였다. 사람의 시각은 영상의 전체적인 품질을 판단하면서도 국부적인 위치에서의 품질을 판단하며, 전체적인 영상의 품질보다는 국부적인 위치에서의 품질이 시각적인 영상품질 판단에 미치는 영향이 크다. 본 논문에서는 영상을 세그먼트화하고 각 세그먼트화된 영상에서 얻어진 영상 품질 값에 스코어링을 하는 통계적 기법을 사용하여 시각에 의한 판단과 유사한 결과를 얻었다.

• 한국멀티미디어학회논문지
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• 제18권9호
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• pp.1008-1018
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• 2015

In this paper, we propose a method that constructs a saliency map in which important regions are accurately specified and the colors of the regions are less influenced by the similar surrounding colors. Our method utilizes LBP(Local Binary Pattern) histogram information to compare and analyze texture information of surrounding regions in order to reduce the effect of color information. We extract the saliency of stereoscopic images by integrating a 2D saliency map with depth information of stereoscopic images. We then measure the distance between two different sizes of the LBP histograms that are generated from pixels. The distance we measure is texture difference between the surrounding regions. We then assign a saliency value according to the distance in LBP histogram. To evaluate our experimental results, we measure the F-measure compared to ground-truth by thresholding a saliency map at 0.8. The average F-Measure is 0.65 and our experimental results show improved performance in comparison with existing other saliency map extraction methods.

• Journal of Mechanical Science and Technology
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• 제18권1호
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• pp.132-144
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• 2004

This paper presents a new method driving multiple robots to their goal position without collision. To consider the movement of the robots in a work area, we adopt the concept of avoidability measure. The avoidability measure figures the degree of how easily a robot can avoid other robots considering the velocity of the robots. To implement the concept to avoid collision among multiple robots, relative distance between the robots is proposed. The relative distance is a virtual distance between robots indicating the threat of collision between the robots. Based on the relative distance, the method calculates repulsive force against a robot from the other robots. Also, attractive force toward the goal position is calculated in terms of the relative distance. These repulsive force and attractive force are added to form the driving force for robot motion. The proposed method is simulated for several cases. The results show that the proposed method steers robots to open space anticipating the approach of other robots. In contrast, since the usual potential field method initiates avoidance motion later than the proposed method, it sometimes fails preventing collision or causes hasty motion to avoid other robots. The proposed method works as a local collision-free motion coordination method in conjunction with higher level of task planning and path planning method for multiple robots to do a collaborative job.

• 대한임베디드공학회논문지
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• 제12권4호
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• pp.231-238
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• 2017

Detecting small infrared targets from the low-SCR images at a long distance is very hard. The previous Local Contrast Method (LCM) algorithm based on the human visual system shows a superior performance of detecting small targets by a background suppression technique through local contrast measure. However, its slow processing speed due to the heavy multi-scale processing overhead is not suitable to a variety of real-time applications. This paper presents a lightweight real-time small target detection algorithm, called by the Improved Selective Local Contrast Method (ISLCM), to reduce the scale-invariant computational overhead. The proposed ISLCM applies the improved local contrast measure to the predicted selective region so that it may have a comparable detection performance as the previous LCM while guaranteeing low scale-invariant computational load by exploiting both adaptive scale estimation and small target feature feasibility. Experimental results show that the proposed algorithm can reduce its computational overhead considerably while maintaining its detection performance compared with the previous LCM.

• 한국식생활문화학회지
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• 제21권1호
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• pp.65-70
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• 2006

The purpose of this study were to measure brand personalities of deluxe hotels in Seoul, and to identify the difference of brand personality between local and international hotels. The questionnaires developed for this study were distributed to 460 employees in kitchen and F&B departments of 11 deluxe hotels in Seoul. A total of 398 questionnaires were used for anaylsis(86.5%) and the statistical analyses were completed using SPSS Win(12.0) for descriptive analysis, reliability analysis and t-test, and AMOS(5.0) for confirmatory factor analysis. The results of this study showed that deluxe hotels have brand personalities relatively strong at 'affection', 'sophistication', 'competence' dimensions, and there was a significant difference by hotel nationality. The brand personality scores of international brand hotels perceived by employees were high at the 'excitement'(p<0.001), 'sophistication'(p<0.001), and 'competence'(p<0.01) dimensions, whereas local hotels were considered more obedient(p<0.01). Overall, it could be a key factor for successful brand management that establish a distinctive brand personality, and a localized brand personality measure will lead to more desirable decision making.

• Journal of the Korean Statistical Society
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• 제33권2호
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• pp.233-244
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• 2004

The influence of observations is investigated in fitting proportional covariance matrices model. Local influence measures are obtained when all parameters or subsets of the parameters are of interest. We will also derive the local influence measure for investigating the influence of observations in testing the proportionality of covariance matrices. A numerical example is given for illustration.

• Journal of information and communication convergence engineering
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• 제9권2호
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• pp.207-211
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• 2011

This paper presents a method for facial feature representation and recognition from the Covariance Matrices of the Gabor-filtered images. Gabor filters are a very powerful tool for processing images that respond to different local orientations and wave numbers around points of interest, especially on the local features on the face. This is a very unique attribute needed to extract special features around the facial components like eyebrows, eyes, mouth and nose. The Covariance matrices computed on Gabor filtered faces are adopted as the feature representation for face recognition. Geodesic distance measure is used as a matching measure and is preferred for its global consistency over other methods. Geodesic measure takes into consideration the position of the data points in addition to the geometric structure of given face images. The proposed method is invariant and robust under rotation, pose, or boundary distortion. Tests run on random images and also on publicly available JAFFE and FRAV3D face recognition databases provide impressively high percentage of recognition.