• Journal of Global Scholars of Marketing Science
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• v.15 no.2
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• pp.49-69
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• 2005

This study is to investigate causal relationship among store image, private brand image and purchase intentions through comparing national distributors with local distributors in Pusan city. More specifically, the objective of this study can be explained as follows; First, what store image have an effect on private brand image. Second, individual store image and their private brand image have different effects. Last, store image and private brand image influence purchase intention of private brands. The results of this study suggests a positive relationship between consumers' perceptions of individual private brands and their associated store image dimensions and purchase intentions toward private brands. A key implication of this research suggests it is desirable for retailers to build up a positive consumer's perceptions of private brand by improving store image. Especially, it is suggested that through the development of specific features of store images, retailers are to manage private brands.

• Proceedings of the Korean Fiber Society Conference
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• 1998.04a
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• pp.296-300
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• 1998

섬유산업내의 정보를 수집하고 체계화하여 경쟁력이 있는 제품을 생산해 내는데 있어서 데이타 베이스를 제공하는 일은 중요하다. 그 일부로서 제품의 경쟁력과 부가가치를 향상시킬수 있는 상표가 가지는 영향은 매우 크다고 볼 수 있다. 따라서 국내외 많은 선행 연구자들은 상표의 인지도, 상표 이미지와 상표 포지셔닝에 관하여 연구하였으며 의복의 구매행동과의 관련성을 규명하고자 하였다.[1,3,5](중략)

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.489-492
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• 2007

산업재산권중 하나인 상표에 대한 효율적인 이미지 검색은 상표도용 및 이로 인한 분쟁을 방지할 수 있다. 이를 위해서는 효율적인 내용기반 유사이미지 검색이 필요하다. 본 논문에서는 상표이미지검색에 있어 가시적인 특성(visual feature)을 그레이 히스토그램을 통해서 상표이미지의 특성값을 추출하여 이를 입력패턴으로 SOM(Self-Organizing Map)알고리즘을 적용한 내용기반 유사이미지 검색시스템을 제안한다.

• Management & Information Systems Review
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• v.38 no.3
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• pp.55-80
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• 2019

Recently, many companies improving their management performance by building a powerful brand value which is recognized for trademark rights. However, as growing up the size of online commerce market, the infringement of trademark rights is increasing. According to various studies and reports, cases of foreign and domestic companies infringing on their trademark rights are increased. As the manpower and the cost required for the protection of trademark are enormous, small and medium enterprises(SMEs) could not conduct preliminary investigations to protect their trademark rights. Besides, due to the trademark image search service does not exist, many domestic companies have a problem that investigating huge amounts of trademarks manually when conducting preliminary investigations to protect their rights of trademark. Therefore, we develop an intelligent similar trademark search model to reduce the manpower and cost for preliminary investigation. To measure the performance of the model which is developed in this study, test data selected by intellectual property experts was used, and the performance of ResNet V1 101 was the highest. The significance of this study is as follows. The experimental results empirically demonstrate that the image classification algorithm shows high performance not only object recognition but also image retrieval. Since the model that developed in this study was learned through actual trademark image data, it is expected that it can be applied in the real industrial environment.

• Journal of Platform Technology
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• v.8 no.1
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• pp.16-23
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• 2020

For protecting copyright for trademark, convolutional neural network can be used to confirm genuine of trademark image. For this, repeated training one trademark image degrades the performance of machine learning because of overfitting problem. Therefore, this type of machine learning application generates training data in various way. But if genuine trademark image is rotated, this image is classified as not genuine trademark. In this paper, we propose the way for extending training data to confirm genuine of trademark image which is rotated. Our proposed way generates rotated image from genuine trademark image as training data. To show effectiveness of our proposed way, we use CNN machine learning model, and evaluate the accuracy with test image. From evaluation result, our way can be used to generate training data for machine learning application which confirms genuine of rotated trademark image.

• The Inventors News
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• no.33
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• pp.2-2
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• 2005

인기 영화나 드라마 제목을 상표로 출원 - 천주교회, 이미지 단일화 위해 그림표지 상표 등록 - 전남 장흥군 `정남진` 상표등록 논란 - 현금영수증 특허권 시비 붙었다 - 옥시, 유사 상표권 분쟁 항소심에서도 `승소`

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.848-851
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• 2019

이미지 형식으로 등록되는 상표의 특성상 상표의 검색에는 어려움이 따른다. 특허청은 도형 상표의 검색을 용이하게 하기 위해 상표가 포함하고 있는 구성요소에 도형분류코드를 부여한다. 하지만 도형 상표에 포함된 이미지를 확인하고 분류코드를 부여하는 과정은 사람이 직접 수행해야 한다는 어려움이 따른다. 이에 본 논문에서는 딥러닝을 이용하여 자동으로 도형 상표 내 객체를 인식하고 분류코드를 부여하는 방안을 제안한다. DenseNet을 이용하여 중분류를 먼저 예측한 후 각 중분류에 해당하는 Faster R-CNN 모델을 이용하여 세분류 예측을 수행하였다. 성능평가를 통해 비엔나분류 중분류별 평균 74.49%의 예측 정확도를 확인하였다.

• Journal of Distribution Research
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• v.9 no.2
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• pp.101-122
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• 2004

In this study, two alternative models are developed and tested in order to investigate the relationship between retailer image and its private brand attitude. The halo effect model hypothesizes that retailer image is related as a halo in private brand evaluation and the summary construct model hypothesizes that retailer image functions as a summary construct of private brand evaluation. The results indicate there are moderating effects of 1) familiarity with a private brand and 2) the characteristics of a product category High familiarity is related with the summary construct model and low familiarity the halo effect model. In private brand food, the summary construct model fits better and explains more adequately that private brand evaluation influences retailer image as a summary construct. In private brand clothes, however, the halo effect model performs better in explaining the relationship between retailer image and private brand attitude.

• Journal of the Korean Society for information Management
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• v.24 no.3
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• pp.321-341
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• 2007

It will be possible to prevent the infringement of the trademarks and the insueing disputes regarding the originality of the trademarks by using an efficient content-based trademark image retrieval system. In this paper, we describe a content-based image retrieval system using the Self Organizing Map(SOM) algorithm. The SOM algorithm utilizes the visual features, which were derived from the gray histogram representation of the images. In addition, we made the objective effectiveness evaluation possible by coming up with a quantitative measure to gauge the effectiveness of the content-based image retrieval system.

• Journal of the Korean Society of Clothing and Textiles
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• v.24 no.8
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• pp.1197-1208
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• 2000

The purpose of this study was to find out the effects of the accord between consumers benefit factors and attribute factors of brand image on brand attitude. This study was based on Kellers conceptualizing model of brand image. The subjects were 605 working women in their twenties living in Seoul, Korea. The data were analyzed by Euclidian distance model, ANOVA of repeated measures, regression, F-test by Extra Sum of Squares Principle. The results were as follows. 1. There were significant differences among the brands and among the segmented groups in the accord between benefit factors and attribute factors of brand image and in the brand preference. Moreover there were significant interactions between the brands and the segmented groups in the accord between benefit factors and attribute factors of brand image and in the brand preference. 2. There were significant effects of the accord between benefit factors and attribute factor of brand image on brand attitude. 3. There were significantly different effects of the accord between benefit factors and attribute factors of brand image on brand attitude among the segmented groups.