• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1498-1504
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• 2016

The progress of mobile computing technology is bringing a large amount of multimedia contents such as image. Thus, we need an image retrieval system which searches semantically relevant image. In this paper, we propose a semantic image annotation and retrieval in mobile environments. Previous mobile-based annotation approaches cannot fully express the semantics of image due to the limitation of current form (i.e., keyword tagging). Our approach allows mobile devices to annotate the image automatically using the context-aware information such as temporal and spatial data. In addition, since we annotate the image using RDF(Resource Description Framework) model, we are able to query SPARQL for semantic image retrieval. Our system implemented in android environment shows that it can more fully represent the semantics of image and retrieve the images semantically comparing with other image annotation systems.

• Korean Journal of Remote Sensing
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• v.31 no.1
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• pp.1-9
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• 2015

Mobility and cloud platform have become the dominant paradigm to develop web services dealing with huge and diverse digital contents for scientific solution or engineering application. These two trends are technically combined into mobile cloud computing environment taking beneficial points from each. The intention of this study is to design and implement a mobile cloud application for remotely sensed image fusion for the further practical geo-based mobile services. In this implementation, the system architecture consists of two parts: mobile web client and cloud application server. Mobile web client is for user interface regarding image fusion application processing and image visualization and for mobile web service of data listing and browsing. Cloud application server works on OpenStack, open source cloud platform. In this part, three server instances are generated as web server instance, tiling server instance, and fusion server instance. With metadata browsing of the processing data, image fusion by Bayesian approach is performed using functions within Orfeo Toolbox (OTB), open source remote sensing library. In addition, similarity of fused images with respect to input image set is estimated by histogram distance metrics. This result can be used as the reference criterion for user parameter choice on Bayesian image fusion. It is thought that the implementation strategy for mobile cloud application based on full open sources provides good points for a mobile service supporting specific remote sensing functions, besides image fusion schemes, by user demands to expand remote sensing application fields.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.12
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• pp.2498-2504
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• 2009

The fundamental research for the mobile robot navigation using the numerical optimization method is presented. We propose an image-based visual servo navigation algorithm for a wheeled mobile robot utilizing a ceiling mounted camera. For the image-based visual servoing, we define the composite image Jacobian which represents the relationship between the speed of wheels of a mobile robot and the robot's overall speed in the image plane. The rotational speed of wheels of a mobile robot can be directly related to the overall speed of a mobile robot in the image plane using the composite image Jacobian. We define the mobile robot navigation problem as an unconstrained optimization problem to minimize the cost function with the image error between the goal position and the position of a mobile robot. In order to avoid the obstacle, the modified cost function is proposed which is composed of the image error between the position of a mobile robot and the goal position and the distance between the position of a mobile robot and the position of the obstacle. The performance was evaluated using the simulation.

• Journal of the Semiconductor & Display Technology
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• v.13 no.4
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• pp.91-96
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• 2014

Mobile image retrieval is one of the most exciting and fastest growing research fields in the area of multimedia technology. As the amount of digital contents continues to grow users are experiencing increasing difficulty in finding specific images in their image libraries. This paper proposes a new efficient and effective mobile image retrieval method that applies a weighted combination of color and texture utilizing spatial-color and second order statistics. The system for mobile image searches runs in real-time on an iPhone and can easily be used to find a specific image. To evaluate the performance of the new method, we assessed the iPhone simulations performance in terms of average precision and recall using several image databases and compare the results with those obtained using existing methods. Experimental trials revealed that the proposed descriptor exhibited a significant improvement of over 13% in retrieval effectiveness, compared to the best of the other descriptors.

• Current Optics and Photonics
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• v.2 no.5
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• pp.453-459
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• 2018

We have developed a high-performance signal-processing and image-rendering heterogeneous computation system for optical coherence tomography (OCT) on mobile processor. In this paper, we reveal it by demonstrating real-time OCT image processing using a Snapdragon 800 mobile processor, with the introduction of a heterogeneous image visualization architecture (HIVA) to accelerate the signal-processing and image-visualization procedures. HIVA has been designed to maximize the computational performances of a mobile processor by using a native language compiler, which targets mobile processor, to directly access mobile-processor computing resources and the open computing language (OpenCL) for heterogeneous computation. The developed mobile image processing platform requires only 25 ms to produce an OCT image from $512{\times}1024$ OCT data. This is 617 times faster than the naïve approach without HIVA, which requires more than 15 s. The developed platform can produce 40 OCT images per second, to facilitate real-time mobile OCT image visualization. We believe this study would facilitate the development of portable diagnostic image visualization with medical imaging modality, which requires computationally expensive procedures, using a mobile processor.

• The Research Journal of the Costume Culture
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• v.28 no.1
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• pp.15-29
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• 2020

Purpose of the study is to explore the effect of the types of mobile coupons(text- vs. image-focused coupons; free-gift vs. discount coupons) on characteristic perception of mobile coupons, and the causal relationships among characteristic perception, attitude, and use intention of mobile coupons. A total of 140 university students participated in experiments with questionnaires including one of the four stimuli. Important findings are as follows. First, image-focused mobile coupons generated more enjoyment than did text-focused coupons. However, the text/image-focused coupons were not different in perception of informativeness and credibility of mobile coupons. Second, enjoyment perception was significantly increased when image-focused contents were combined with discount coupons whereas enjoyment perception was decreased when text-focused contents were combined with free-gift coupons. This interaction effect reflects that the level of enjoyment of consumers can be changed in terms of the combination of the value-provision types of coupons and the text-image focused contents. Third, it was found that consumer perception of coupon characteristics formed attitudes toward mobile coupons, and use intention of mobile coupons was determined by attitudes toward mobile coupons. Study findings may fill the void of research investigating the effect of text-image contents and the types of coupons on consumer reponses toward mobile coupons. Mobile coupons have limited quantity of information within a small size of mobile phone screen, therefore, the results were not consistent with prior research tested with mobile advertisements indicating the effect of text-image contents on perception of informativeness and credibility.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.237-243
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• 2014

In this paper, we propose a mobile image retrieval system which utilizes the mobile device's sensor information and enables running in a variety of the environments, and implement the system on Android platform. The proposed system deals with a new image descriptor using combination of the visual feature with EXIF attributes in the target of JPEG image, and image matching algorithm which is optimized to the mobile environments. Experiments are performed on the Android platform, and the experimental results revealed that the proposed algorithm exhibits a significant improved results with large image database.

• Journal of the Semiconductor & Display Technology
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• v.14 no.2
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• pp.53-59
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• 2015

Since the amount of digital image continues to grow in usage, users feel increased difficulty in finding specific images from the image collection. This paper proposes a novel image searching scheme that extracts the image feature using combination of Advanced SURF (Speed-Up Robust Feature) and DCD (Dominant Color Descriptor). The key point of this research is to provide a new feature extraction algorithm to improve the existing SURF method with removal of unnecessary feature in image retrieval, which can be adaptable to mobile system and efficiently run on the mobile environments. To evaluate the proposed scheme, we assessed the performance of simulation in term of average precision and F-score on two databases, commonly used in the field of image retrieval. The experimental results revealed that the proposed algorithm exhibited a significant improvement of over 14.4% in retrieval effectiveness, compared to OpenSURF. The main contribution of this paper is that the proposed approach achieves high accuracy and stability by using ASURF and DCD in searching for natural image on mobile platform.

• Journal of Internet Computing and Services
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• v.11 no.2
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• pp.173-184
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• 2010

The advancement of ubiquitous networks facilitates and increases access to the Internet via mobile devices, which offers the advantages of enhanced mobility and accessibility. While Mobile Internet is largely free of temporal and spatial restrictions, producing content for mobile websites is a challenging work due to the existence of multiple device types and markup languages. This paper proposes a technique that makes use of image maps to improve the visual consistency of mobile web content displayed on a variety of mobile devices. The proposed image map method captures several objects comprising the webpage into a single image, and provides the image in Mobile Web services. Mobile devices employing the proposed method can reorganize webpages with multiple objects more easily and obtain the visually identical content on their screen.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.1077-1080
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• 2009

In this paper, we propose a new method for measuring image sticking of an OLED display using a human visual test. We determined that the perceptual image sticking threshold is 2% of luminance difference at 200 nits and 1% at 100 nits, respectively. Color shift must also be considered when evaluating image sticking, as a ${\Delta}$(u', v') shift of just over 0.002 can be recognized regardless of background brightness. Perception of image sticking is affected by the background level, test pattern, and ambient illumination conditions. The evaluation standard must consider both luminance variation and color shift simultaneously.