• Journal of dental hygiene science
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• v.15 no.6
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• pp.689-695
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• 2015

The aim of this study was to examine the image for dental hygienists and career consideration in academic high school students. A self-reported questionnaire was surveyed by 199 high school students in Gwangju. The questionnaire composed subject's general characteristics, image for dental hygienists, career consideration. The data were analyzed for independent t-test or Mann-Whitney test, one-way ANOVA or Kruskal wallis test and pearson's correlation coefficient by using IBM SPSS Statistics ver. 21.0 program. The average of total image was 3.36, personal images were 3.64, occupational images were 3.47, business images were 3.42, social images were 2.83 in the five-point scale. The image of dental hygienists was higher significantly in case of having a dental practitioner in the family, treatment experience less than 1 year, and treatment in dental hospital. The participants who considered to be dental hygienist were higher significantly in occupational and social images. There were positive correlations among the personal, occupational, business, social images of dental hygienists. These results showed that general images for dental hygienists were slightly positive but among them, social image was the lowest level. It showed that most students didn't consider to be dental hygienist. Therefore, we suggested to enhance positive recognition for dental hygienists be needed.

• Annual Conference of KIPS
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• 2013.11a
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• pp.1394-1396
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• 2013

플리커와 같은 대용량 영상저장 및 공유 사이트가 인기를 끌면서 이미지 정보의 양은 점점 늘어나고 있고 사용자들은 정확한 이미지 정보 검색을 요구하고 있다. 태그기반의 이미지 검색에서 정확도를 높이기 위하여 태그들의 의미적 연관성을 이용하는 등 다양한 연구가 진행되고 있다. 본 논문에서는 특징점 추출에 기반하여 이미지를 분류하는데 뛰어난 성능을 가진 SIFT알고리즘을 사용하여 플리커 이미지를 분류하는 방법을 제안한다. 위키피디아 의미 연관성을 이용해 태그 정보로 1차 분류된 데이터베이스에 SIFT알고리즘을 사용해본 결과 기존의 SURF를 사용한 연구보다 높은 정확성을 보이는 것을 확인하였다. 따라서 이 방법을 통하여 다양한 이미지를 더욱 정확하게 분류할 수 있을 것으로 기대한다.

• Archives of design research
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• v.15 no.4
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• pp.327-336
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• 2002

This paper is intended to help cool-skin-colored people to choose suitable clothing colors confidently and look well-dressed and to make positive self-images. A pseudo-experimental method has made it possible to analyze the visual evaluations of clothing color images for cool-skin-colored people and obtain the following results. 1. Reddish colors of vivid tone for doffing give positive images and those of dull and dark tone, negative ones. 2. Yellowish colors of vivid and bright tone for doffing show positive images and those of dull and dark tone, negative ones. Cool yellow of light tone proves to contribute to a well-looking image. 3. Warm green of vivid and deep tone, and cool green of vivid tone for clothing present positive images. 4. Warm blue of vivid and deep tone, and cool blue of vivid and bright lone make positive images. Either blue with dull tone gives a negative image. 5. Purple colors whose tone is vivid, deep and light contribute to positive images, and those of dull tone, negative ones.

• KIISE Transactions on Computing Practices
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• v.22 no.6
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• pp.290-295
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• 2016

Recently, folksonomy-based image-sharing sites where users cooperatively make and utilize tags of image annotation have been gaining popularity. Typically, these sites retrieve images for a user request using simple text-based matching and display retrieved images in the form of photo stream. However, these tags are personal and subjective and images are not categorized, which results in poor retrieval accuracy and low user satisfaction. In this paper, we propose a categorization scheme for folksonomy images which can improve the retrieval accuracy in the tag-based image retrieval systems. Consequently, images are classified by the semantic similarity using text-information and image-information generated on the folksonomy. To evaluate the performance of our proposed scheme, we collect folksonomy images and categorize them using text features and image features. And then, we compare its retrieval accuracy with that of existing systems.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.533-540
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• 2002

We can buy products everywhere from Web-based shopping mall using desktop, cellular phone or PDA. To guarantee the various services for different equipment, shopping mail systems should allow a lot of different size or quality of images to provide a good service to their customers. Despite of same product image, each shopping mall saves the image in its storage space individually. Furthermore, all the product images in each shopping mall are stored as images of different quality. It may waste resources of shopping mail server and bring us developmental overhead. It is difficult to update all the images for product that is used by distributed e-catalog in everywhere. In this paper, we extended the proposed Web Image Server (WIS) for sharing one image with all clients and processing Image dynamically, so that we strengthened the function of managing shopping mall as a client of WIS and added the function of recording clients'log file and image catalog for shopping mall. We measured the response time from WIS and conventional e-Commerce site using by WAS which is one of the stress test tools for Web application. Furthermore, we measured WIS responses image requests in reasonable time when the current user is increased.

• Journal of the Korean Society for Library and Information Science
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• v.47 no.3
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• pp.321-342
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• 2013

The purpose of this study was to compare and evaluate retrieval effectiveness of three types of image perception using different retrieval methods. Image types included specific, general, and abstract topics. The retrieval method included text only search, query by example (QBE) search, and a hybrid/hybrid search. Thirty-two college students were recruited for searching topics using Google image search system. The search results were compared with One-Way and Two-Way ANOVA. As a result, text search and hybrid search showed advantage when searching for specific and general topics. On the other hand, the QBE search performed better than both the text-only and hybrid search for abstract topics. The results have implications for the implementation of image retrieval systems.

• The Journal of the Korea Contents Association
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• v.20 no.7
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• pp.86-96
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• 2020

Based on the use cases of image recognition technology, this study looked at how artificial intelligence plays a role in image recognition technology. Through image recognition technology, satellite images can be analyzed with artificial intelligence to reveal the calculation of oil storage tanks in certain countries. And image recognition technology makes it possible for searching images or products similar to images taken or downloaded by users, as well as arranging fruit yields, or detecting plant diseases. Based on deep learning and neural network algorithms, we can recognize people's age, gender, and mood, confirming that image recognition technology is being applied in various industries. In this study, we can look at the use cases of domestic and overseas image recognition technology, as well as see which methods are being applied to the industry. In addition, through this study, the direction of future research was presented, focusing on various successful cases in which image recognition technology was implemented and applied in various industries. At the conclusion, it can be considered that the direction in which domestic image recognition technology should move forward in the future.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.551-555
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• 2010

In protein 2-DE image analysis, the accuracy of spot-matching operation which identifies the spot of the same protein in each 2-DE gel image is intensively influenced by the errors caused by the various experimental conditions. This paper proposes an efficient method to find more accurate spot-matching patterns based on multiple reference gel images in spot-matching pattern analysis in protein 2-DE image analysis. Additionally, in order to improve the reduce the execution time which is increased exponentially along with the increasing number of gel images, a "partition then extension" framework is used to find spot-matching pattern of long length and of higher accuracy. In the experiments on real 2-DE images of human liver tissue are used to confirm the accuracy and the efficiency of the proposed algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.8
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• pp.1941-1947
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• 2014

Document image binarization is largely used as previous stage of document recognition. And the result of document recognition is much affected from the result of document image binarization. There were many studies to binarize document images. The results of previous studies for document image binarization is varied according to the state of document images. In this paper, we propose a technique for document image binarization using MSER that is applied to extract objects from an image. At first, raw MSER objects are extracted from a document image. Because the raw MSER objects cannot be used for document image binarization, the extracted raw MSER objects are modified. Then the final MSER objects are used for document image binarization with the contrast image that is extracted from the document image. Experimental results show that the proposed technique is useful for document image binarization.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.1
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• pp.64-77
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• 2012

In this study, the crack detecting system with digital image processing techniques based on the mathematical morphology method was developed to detect cracks in concrete structures. In the developed system, the image combining technique of reconstructing multiple images as an entire single image considering efficient management of analysis results was applied as an additional module. The developed system was verified through a field test with the cracked concrete culvert and the crack width of 0.2 mm was able to be detected in the 40m span. In the image analysis, the difference between calculated crack width and actual crack width were less than 0.08mm. For image combination in the stitching test of pattern images, the stitched image was identical with the original picture of entire subject in the visual perception level.