• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1707-1710
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• 2003

In this paper, we propose a method of decision on blurring for business card images using block classification. In the proposed method, an input image is partitioned into 8${\times}$8 blocks and each block is classified into character block or background block using a block energy calculated in DCT domain. Whether the input image is blurring or non-blurring is determined using a ratio of low frequency energy and high frequency energy in DCT domain. Experimental results show that the proposed block classification classifies block well and the proposed decision on blurring decides well for various business card images.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2128-2131
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• 2003

We present an efficient algorithm for skew correction of business card images obtained by a PDA camera. The proposed method is composed of four parts: block adaptive binarization (BAB), stripe generation, skew angle calculation, and image rotation. In the BAB, an input image is binarized block by block so as to lessen the effects of irregular illumination and shadows over the input image. In the stripe generation, character string clusters are generated merging character strings and their inter-spaces, and then only clusters useful for skew angle calculation are output as stripes. In the skew angle calculation, the direction angles of the stripes are calculated using their central moments and then the skew angle of the input image is determined averaging the direction angles. In the image rotation, the input image is rotated by the skew angle. Experimental results shows that the proposed method yields correction rates of 97％ for business card images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.34-40
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• 2023

A smart business card printing system that automatically prints business cards requested by customers online is being activated. What matters is that the business card submitted by the customer to the system may be abnormal. This paper deals with the problem of determining whether the image of a business card has been abnormally rotated by adopting artificial intelligence technology. It is assumed that the business card rotates 0 degrees, 90 degrees, 180 degrees, and 270 degrees. Experiments were conducted by applying existing VGG, ResNet, and DenseNet artificial neural networks without designing special artificial neural networks, and they were able to distinguish image rotation with an accuracy of about 97%. DenseNet161 showed 97.9% accuracy and ResNet34 also showed 97.2% precision. This illustrates that if the problem is simple, it can produce sufficiently good results even if the neural network is not a complex one.

• Asia Marketing Journal
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• v.14 no.3
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• pp.153-167
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• 2012

KB Kookmin Card has separated as an independent corporation from KB Kookmin Bank Credit Card Business Group on March, 2011. Ever since, KB Kookmin Card worked to build its own brand identity. The strategic preparation and conscientious implementations made KB Kookmin Card position in consumer's mind with a strong and unique brand image. Its new brand image was rooted in the inherited strengths of reliable and sincere image. However, it faced the challenge to compete in credit card industry in which most competitors had an advanced and sophisticated image. The strengths of KB Kookmin Card were also at the same time their limitations. KB Kookmin Card took a strategy that strengthened the strengths and improved the weaknesses. It focused on the core competence of being a people's sincere life supporter that helps people make savings from everyday events to make a good sum rather than being a lump sum benefit. The brand introduction strategy was implemented in 2011. The implementation focused on the activities that made internal as well as external customers be aware of the brand. Communication programs using a variety of media were executed to attain this goal. In 2012, second phase communication programs were introduced to elaborate the newly established brand image. It introduced many extended products as well as accessory programs which targeted the segments. Also, various CSR activities in many social domains helped consumers and the public to consider KB Kookmin Card an authentic, caring, trustworthy, and consistently-developing supporter in their everyday lives.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.722-727
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• 2010

This paper is presented to study simplification of face image using cubic spline interpolation for a business card with 2D barcode. People often forget business card's owner because business cards don't be included a face picture generally. To solve such problem, many applications have be developed through mobile devices, Internet and so on. But they couldn't caught up with value of existing business card mad by paper. Hence, some methods which can put information on business card using 1D or 2D barcode had suggested. but they couldn't include information like face image or company logo image which have too much data. Therefore, we study the simplification method of face image to encode from a face image to 2D barcode. The simplification method using spline curves defined by feature points which we dotted on face, ears, hair, eyebrows, nose, lips, neck, etc.. on a face area. for experiment, we see real face image and simplified face image made by proposed method after we automatically extract face watch through camera. In experimental results, data of simplified face image was reduced as small as it can be expressed by 2D barcode, and confirmed that it can effectively express features.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.2
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• pp.318-328
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• 2014

In this paper, as a way of performance improvement of business card recognition in the mobile environment, we suggested a hybrid OCR agent which combines data using a parallel processing sequence between various algorithms and different kinds of business card recognition engines which have learning data. We also suggested an Image Processing Method on mobile cameras which adapts to the changes of the lighting, exposing axis and the backgrounds of the cards which occur depending on the photographic conditions. In case a hybrid OCR agent is composed by the method suggested above, the average recognition rate of Korean business cards has improved from 90.69% to 95.5% compared to the cases where a single engine is used. By using the Image Processing Method, the image capacity has decreased to the average of 50%, and the recognition has improved from 83% to 92.48% showing 9.4% improvement.

• Journal of Korean Society for Quality Management
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• v.46 no.4
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• pp.1015-1028
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• 2018

Purpose: This study attempts to find how the cultural marketing activities utilizing cultural space affect firm's brand image and brand loyalty, and whether this culture marketing technique is recognized as a social contribution activity by potential customers and thereby influence brand image and loyalty. Methods: The data was collected by using the structured questionnaires to consumers who have experience using the Naver Library, Starfield Library, and Hyundai Card Library. The proposed research model is tested using 178 valid questionnaires using Smart PLS 2.0. Results: This research indicated that among cultural marketing factors, cultural support and cultural promotion have little impact on brand image, whereas culture firm influence brand image. Brand image also had an impact on brand loyalty, but it was found that public libraries operated by companies were not recognized as corporate social contribution activities, nor did they have an impact on the formation of the company's brand image. Conclusions: The study offered a theoretical and empirical foundation for future research by empirically identifying the relationship between cultural marketing and brand image and loyalty and confirmed the coordinating effect of social contribution activities between a cultural firm and its brand image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6C
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• pp.801-814
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• 2004

In this paper, we propose a block adaptive binarization (BAB) using a modified quadratic filter (MQF) to binarize business card images acquired by personal digital assistant (PDA) cameras effectively. In the proposed method, a business card image is first partitioned into blocks of 8${\times}$8 and the blocks are then classified into character Hocks (CBs) and background blocks (BBs). Each classified CB is windowed with a 24${\times}$24 rectangular window centering around the CB and the windowed blocks are improved by the pre-processing filter MQF, in which the scheme of threshold selection in QF is modified. The 8${\times}$8 center block of the improved block is barbarized with the threshold selected in the MQF. A binary image is obtained tiling each binarized block in its original position. Experimental results show that the MQF and the BAB have much better effects on the performance of binarization compared to the QF and the global binarization (GB), respectively, for the test business card images acquired in a PDA. Also the proposed BAB using MQF gives binary images of much better quality, in which the characters appear much better clearly, over the conventional GB using QF. In addition, the binary images by the proposed BAB using MQF yields about 87.7% of character recognition rate so that about 32.0% performance improvement over those by the GB using QF yielding about 55.7% of character recognition rate using a commercial character recognition software.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.1-23
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• 2019

Big data refers to data that is difficult to store, manage, and analyze by existing software. As the lifestyle changes of consumers increase the size and types of needs that consumers desire, they are investing a lot of time and money to understand the needs of consumers. Companies in various industries utilize Big Data to improve their products and services to meet their needs, analyze unstructured data, and respond to real-time responses to products and services. The financial industry operates a decision support system that uses financial data to develop financial products and manage customer risks. The use of big data by financial institutions can effectively create added value of the value chain, and it is possible to develop a more advanced customer relationship management strategy. Financial institutions can utilize the purchase data and unstructured data generated by the credit card, and it becomes possible to confirm and satisfy the customer's desire. CRM has a granular process that can be measured in real time as it grows with information knowledge systems. With the development of information service and CRM, the platform has change and it has become possible to meet consumer needs in various environments. Recently, as the needs of consumers have diversified, more companies are providing systematic marketing services using data mining and advanced CRM (Customer Relationship Management) techniques. KB Kookmin Card, which started as a credit card business in 1980, introduced early stabilization of processes and computer systems, and actively participated in introducing new technologies and systems. In 2011, the bank and credit card companies separated, leading the 'Hye-dam Card' and 'One Card' markets, which were deviated from the existing concept. In 2017, the total use of domestic credit cards and check cards grew by 5.6% year-on-year to 886 trillion won. In 2018, we received a long-term rating of AA + as a result of our credit card evaluation. We confirmed that our credit rating was at the top of the list through effective marketing strategies and services. At present, Kookmin Card emphasizes strategies to meet the individual needs of customers and to maximize the lifetime value of consumers by utilizing payment data of customers. KB Kookmin Card combines internal and external big data and conducts marketing in real time or builds a system for monitoring. KB Kookmin Card has built a marketing system that detects realtime behavior using big data such as visiting the homepage and purchasing history by using the customer card information. It is designed to enable customers to capture action events in real time and execute marketing by utilizing the stores, locations, amounts, usage pattern, etc. of the card transactions. We have created more than 280 different scenarios based on the customer's life cycle and are conducting marketing plans to accommodate various customer groups in real time. We operate a smart offering system, which is a highly efficient marketing management system that detects customers' card usage, customer behavior, and location information in real time, and provides further refinement services by combining with various apps. This study aims to identify the traditional CRM to the current CRM strategy through the process of changing the CRM strategy. Finally, I will confirm the current CRM strategy through KB Kookmin card's big data utilization strategy and marketing activities and propose a marketing plan for KB Kookmin card's future CRM strategy. KB Kookmin Card should invest in securing ICT technology and human resources, which are becoming more sophisticated for the success and continuous growth of smart offering system. It is necessary to establish a strategy for securing profit from a long-term perspective and systematically proceed. Especially, in the current situation where privacy violation and personal information leakage issues are being addressed, efforts should be made to induce customers' recognition of marketing using customer information and to form corporate image emphasizing security.

• The Journal of Society for e-Business Studies
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• v.20 no.3
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• pp.11-28
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• 2015

Due to the mobil-centered lifestyle following the wider use of Smartphones, Mobile services, including mobile banking and mobile shopping business have increased rapidly. Also with the emergence of "Fintech", which finance combined with technology, IT based financial market is going to be highly promising. In this trend, interests mobile credit cards are increasing. But diffusion of the mobile credit card services is still in the low level. In this situation, to identify factors that influencing satisfaction and continuous usage intention on mobile credit card, this study applied innovation diffusion theory (IDT) and post acceptance model (PAM). To conducting this research, survey data were collected, and we used SmartPLS to analyze survey data. As a result of the study, perceived easy of use, image, compatibility and facilitation positively affect user's satisfaction in mobile credit cards and that such satisfaction have a positive impact on continuous intention to use. The facilitation influences user satisfaction more strongly for those who use mobile credit cards more than plastic credit cards. Also, perceived of use and image influence user satisfaction more strongly for those who use plastic credit cards more than mobile credit cards. It is expected that this study can be a guideline for credit card service providers and policy makers to invigorate mobile credit card business. Also it worths as a early-stage research on Fintech-related studies.