• Journal of the Korea Computer Industry Society
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• v.7 no.1
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• pp.17-22
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• 2006

Variable contents are extracted and used to improve the correctness of the retrieval in the content-based in age retrieval. This way use the physical feature for the retrieval. In this way of retrieval, the user has to know the basic physical features and spatial relationship of target images that he wants to retrieve. There are some restriction to reflect the user's intend. We need the retrieval system that reflect the user's intend. In this paper, we propose an emotion-based retrieval system. It is different from past emotion based image retrieval in point of view that it uses relevance feedback to estimate the users intend and it is easily combined with past content-based image retrieval system. The features and similarity measures are adopted from MPEG-7 color descriptors which are proper retrieval of large multimedia databases. We use wallpaper images for the experiment. The result shows that the system get successful result.

• Journal of KIISE:Databases
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• v.36 no.6
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• pp.434-445
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• 2009

Content-based image retrieval(CBIR) is the retrieval technique which uses the contents of images. However, in contrast to text data, multimedia data are ambiguous and there is a big difference between system's low-level representation and human's high-level concept. So it doesn't always mean that near points in the vector space are similar to user. We call this the semantic-gap problem. Due to this problem, performance of image retrieval is not good. To solve this problem, the relevance feedback(RF) which uses user's feedback information is used. But existing RF doesn't consider user's region-of-interest(ROI), and therefore, irrelevant regions are used in computing new query points. Because the system doesn't know user's ROI, RF is proceeded in the image-level. We propose a new ROI RF method which guides a user to select ROI from relevant images for the retrieval of complex satellite image, and this improves the accuracy of the image retrieval by computing more accurate query points in this paper. Also we propose a pruning technique which improves the accuracy of the image retrieval by using images not selected by the user in this paper. Experiments show the efficiency of the proposed ROI RF and the pruning technique.

• Journal of KIISE:Databases
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• v.34 no.3
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• pp.193-205
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• 2007

Increasing amount of digital images requires more accurate and faster way of image retrieval. So far, image retrieval method includes content-based retrieval and keyword based retrieval, the former utilizing visual features such as color and brightness and the latter utilizing keywords which describe the image. However, the effectiveness of these methods as to providing the exact images the user wanted has been under question. Hence, many researchers have been working on relevance feedback, a process in which responses from the user are given as a feedback during the retrieval session in order to define user’s need and provide improved result. Yet, the methods which have employed relevance feedback also have drawbacks since several feedbacks are necessary to have appropriate result and the feedback information can not be reused. In this paper, a novel retrieval model has been proposed which annotates an image with a keyword and modifies the confidence level of the keyword in response to the user’s feedback. In the proposed model, not only the images which have received positive feedback but also the other images with the visual features similar to the features used to distinguish the positive image are subjected to confidence modification. This enables modifying large amount of images with only a few feedbacks ultimately leading to faster and more accurate retrieval result. An experiment has been performed to verify the effectiveness of the proposed model and the result has demonstrated rapid increase in recall and precision while receiving the same number of feedbacks.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.61-67
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• 2016

With the current high distribution rate of smart devices and the recent development of computing technology, user interest in multimedia, such as photos, videos, and so on, has rapidly increased, which is a departure from the simple pattern of information retrieval. Because of these increasing interests, image processing techniques, which generate and process images for diverse applications, are being developed. In entertainment recently, there are some techniques that present a celebrity's image as a mosaic comprising many small images. In addition, studies into the mosaic technique are actively conducted. However, conventional mosaic techniques result in a long processing time as the number of database images increases, because they compare the images in the databases sequentially. Therefore, to increase search efficiency, this paper proposes an algorithm to generate a mosaic image using a discrete cosine transform (DCT) hash. The proposed photo mosaic-generation algorithm is composed of database creation and mosaic image generation. In database creation, it first segments images into blocks with a predefined size. And then, it computes and stores a DCT hash set for each segmented block. In mosaic generation, it efficiently searches for the most similar blocks in the database via DCT hash for every block of the input image, and then it generates the final mosaic. With diverse experimental results, the proposed photo mosaic-creation algorithm can effectively generate a mosaic, regardless of the various types of images and sizes.