• 농업과학연구
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• 제49권3호
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• pp.667-678
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• 2022

A characteristic of a region's environmental resources is the competitiveness of local agricultural products. This study explores methods of making locally produced agricultural products appealing to consumers. We looked at ways to appeal to consumers by using the image of environment resource and environment-agriculture product image congruence. The relationships of two dimensions of environmental image, perceived quality and purchase intention, are examined. From the results of the study, both the image of environment resource and environment-agriculture product image congruence have a positive effect on purchasing local agricultural products through perceived quality. This study tried to ascertain which of the two dimensions of the environmental image factor is more effective in terms of consumer appeal for local agricultural products. As a result, both the image of environment resource and environment-agricultural product image congruence are found to have a positive effect on the purchase intention of consumers through perceived quality. By comparing the paths of the two dimensions it is found that the method of appealing to consumers by using the environment-agriculture product image congruence is more effective. The results of this study present an effective method of making locally produced agricultural products appealing to consumers and suggest an effective strategic direction for selling local agricultural products.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제16권9호
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• pp.889-897
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• 2010

현대의 대량화된 영상 관리 시스템은 영상의 특징을 표현하는 영상식별자에 대해 왜곡에 강인하며 빠른 검색 속도, 정확성 및 효율적인 저장 등의 기본 성능을 요구한다. 영상식별자 설계 방법은 기하학적 왜곡에 강인한 지역 방식과 빠른 검색 및 적은 저장 용량의 속성을 지닌 전역방식으로 구분 할 수 있다. 본 논문에서는 왜곡에 강하고 지역적 공간적 제약으로 인한 서로간의 차별성이 강화된 지역 기술자들로부터 각각 개개 차원의 특징 분포도를 분석하여, 두 영상간의 유사도를 빠르고 정확하게 측정할 수 있는 지역 기술자 및 전역 기술자의 속성을 가지고 있는 LFH(Local Feature's Histogram)기반 영상식별자를 제안한다. 또한 GPU를 사용하여 LFH를 구현하는 방법을 제시하며, 제안한 LFH와 대표적인 지역, 전역 방식인 SIFT 및 EHD 방식과 저장용량, 추출 시간, 검색 속도 및 정확률에 대한 성능을 비교하였다.

• Human Ecology Research
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• 제60권4호
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• pp.645-665
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• 2022

This study aimed to understand the effect of the characteristics of the influencer of public officials and the characteristics of internet live broadcasting in China on the brand image of local agricultural products, purchase intention, and word-of-mouth intention. A survey was administered to Chinese consumers who had purchased local agricultural products after watching live broadcasts on the internet by influencers of government officials. A total of 317 questionnaires were collected and the data were analyzed using SPSS 26.0 and AMOS 28.0. The key results were as follows. First, regarding the characteristics of the influencer of public officials, reliability, attractiveness, and expertise had a positive effect on the brand image of local agricultural products. Second, among the characteristics of internet live broadcasting, interaction and information had a positive effect on the brand image of local agricultural products, but entertainment did not. Third, the brand image of local agricultural products had a positive effect on purchase intention and word-of-mouth intention. Finally, the mediating effect of local agricultural brand image was evident in the reliability, attractiveness, and expertise characteristics of the influencer of public officials and purchase intention and word-of-mouth intention. Finally, the mediating effect of local agricultural brand image was evident in the interaction and information characteristics of internet live broadcasting and purchase intention and word-of-mouth intention.

• 문화기술의 융합
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• 제6권1호
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• pp.389-393
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• 2020

세계적으로 로컬기반의 상품, 특히 농식품에 대한 관심과 중요성이 커지고 있는데 비해 이에 대한 체계적인 연구는 여전히 부족한 실정이다. 최근에는 농식품에 대해서도 소비자들이 브랜드를 중요하게 생각하는 경향을 보여주고 있어 로컬푸드와 로컬푸드 브랜드의 관계에 대해 연구를 시작하였다. 본 연구에서는 로컬푸드를 대상으로 로컬푸드상품과 로컬푸드 브랜드에 대한 이미지일치성이 브랜드선호와 구매의도에 미치는 영향을 살펴보았다. 연구의 결과 로컬푸드상품과 브랜드에 대한 이미지일치성이 강할수록 브랜드선호에 긍정적인 영향을 미치는 것으로 나타났다. 또한 브랜드 선호가 강할수록 고객의 재구매의도도 높게 나타났다.

• 한국멀티미디어학회논문지
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• 제18권7호
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• pp.827-833
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• 2015

In this paper, we have compared three level set-based active contour (LSAC) methods on inhomogeneous MR image segmentation which is known as an important role of brain diseases to diagnosis and treatment in early. MR image is often occurred a problem with similar intensities and weak boundaries which have been causing many segmentation methods. However, LSAC method could be able to segment the targets such as the level set based on the local image fitting energy, the local binary fitting energy, and local Gaussian distribution fitting energy. Our implemented and tested the subcortical image segmentations were the corpus callosum and hippocampus and finally demonstrated their effectiveness. Consequently, the level set based on local Gaussian distribution fitting energy has obtained the best model to accurate and robust for the subcortical image segmentation.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 추계종합학술대회 논문집
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• pp.589-592
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• 1999

Matching is a key problem in computer vision, image analysis and pattern recognition. In this paper a multiscale image matching algorithm by wavelet local extrema is proposed. This algorithm is based on the multiscale wavelet transform of the curvature which can utilize both the information of local extrema positions and magnitudes of transform results. This method has advantages in computational cost to a single scale image matching. It is also rotation-, translation-, and scale-independent image matching method. This matching can be used for the recognition of occluded objects.

• Journal of Information Processing Systems
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• 제13권5호
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• pp.1372-1381
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• 2017

In this paper, a texture feature extraction method using local energy and local correlation of Gabor transformed images is proposed and applied to an image retrieval system. The Gabor wavelet is known to be similar to the response of the human visual system. The outputs of the Gabor transformation are robust to variants of object size and illumination. Due to such advantages, it has been actively studied in various fields such as image retrieval, classification, analysis, etc. In this paper, in order to fully exploit the superior aspects of Gabor wavelet, local energy and local correlation features are extracted from Gabor transformed images and then applied to an image retrieval system. Some experiments are conducted to compare the performance of the proposed method with those of the conventional Gabor method and the popular rotation-invariant uniform local binary pattern (RULBP) method in terms of precision vs recall. The Mahalanobis distance is used to measure the similarity between a query image and a database (DB) image. Experimental results for Corel DB and VisTex DB show that the proposed method is superior to the conventional Gabor method. The proposed method also yields precision and recall 6.58% and 3.66% higher on average in Corel DB, respectively, and 4.87% and 3.37% higher on average in VisTex DB, respectively, than the popular RULBP method.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.159-162
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• 2008

This paper presents a modified mean curvature diffusion filter to smooth speckle noise in images. Mean curvature diffusion filter has already shown good results in reducing noise in images while preserving fine details. In the mean curvature diffusion, the rate of smoothing is controlled by the local value of the diffusion coefficient chosen to be a function of the local image gradient magnitude. In this paper, the diffusion coefficient is modified to be controlled adaptively by local image surface slope and heterogeneity. The local surface slope contributes to preserving details (e.g.edges) in image and the local surface heterogeneity helps the smoothing filter consider the amount of noise in both edge and non-edge area. The proposed filter's performance is demonstrated by quantitative experiments using speckle noised aerial image and TerraSAR-X satellite image.

• ETRI Journal
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• 제45권3호
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• pp.505-517
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• 2023

Color, texture, and shape act as important information for images in human recognition. For content-based image retrieval, many studies have combined color, texture, and shape features to improve the retrieval performance. However, there have not been many powerful methods for combining all color, texture, and shape features. This study proposes a content-based image retrieval method that uses the combined local and global features of color, texture, and shape. The color features are extracted from the color autocorrelogram; the texture features are extracted from the magnitude of a complete local binary pattern and the Gabor local correlation revealing local image characteristics; and the shape features are extracted from singular value decomposition that reflects global image characteristics. In this work, an experiment is performed to compare the proposed method with those that use our partial features and some existing techniques. The results show an average precision that is 19.60% higher than those of existing methods and 9.09% higher than those of recent ones. In conclusion, our proposed method is superior over other methods in terms of retrieval performance.

• IEIE Transactions on Smart Processing and Computing
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• 제5권1호
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• pp.49-54
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• 2016

Regarding global and local factors of a set of features, a given single image or multiple images is a common approach in image processing. This paper introduces an application of an adaptive version of non-local filter whose original version searches non-local similarity for removing noise. Since most images involve texture partner in both foreground and background, extraction of signified regions with texture is a challenging task. Aiming to the detection of visual attention regions for images with texture, we present the contrast analysis of image patches located in a whole image but not nearby with assistance of the adaptive filter for estimation of non-local divergence. The method allows extraction of signified regions with texture of images of wild life. Experimental results for a benchmark demonstrate the ability of the proposed method to deal with the mentioned challenge.