• Journal of Advanced Technology Convergence
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• v.2 no.3
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• pp.49-58
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• 2023

This study tried to verify the context effect in cosmetics advertisements by examining the cosmetics advertisement effect according to whether the brand image and the model image matched, and whether the brand image and the advertisement copy were harmoniously perceived. To this end, data were collected using the brand value type (3) × advertisement copy type (3) factorial design. The results are as follows. First, as a result of confirming the advertising effect according to the matching of the cosmetic brand image and the model image, it was found that both the advertising attitude and purchase intention were significantly high when the model image and the brand image matched. Second, it was confirmed whether there was a difference in the advertisement effect according to whether the cosmetic brand image and copy type matched. As a result, consumers who perceived that the cosmetic brand image and copy type matched had significantly higher advertising attitudes and purchase intentions than consumers who perceived that the copy type did not match. It is expected that it will provide validity as to whether the copy strategy should be established by incorporating the context effect when setting up a copy strategy for cosmetics advertisements in the future.

• Journal of The Korean Association For Science Education
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• v.26 no.3
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• pp.406-414
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• 2006

This study investigated 7th grade students' context dependency on explanations about propagating path of light in three different contextual problems: observation of an object, observation of an object's image in a mirror, and observation of one's own face reflection in a mirror. Researchers examined student response in each context through interviews. The students were classified into four groups according to their explanations for the three different contexts. Each group was redivided into two or three subgroups in accordance with their conceptual features. After that, researchers investigated the characteristics of each subgroup. Main findings of the study indicated that (1) group 1 students' conceptions differed in each context; (2) group 2 students showed scientific conceptions in C1 context but in C2 context they showed visual ray conceptions or image misconceptions; (3) group 3 students did not show scientific conceptions in C3 context by strong misconceptions about one's own face reflection in the mirror. Also, this paper discussed the educational implications of the results.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.108-113
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• 2009

Significant attention has recently been drawn to digital home photo albums that use face detection technology. The tendency can be found in home photo albums that people prefer to allocate concerned objects in the center of the image rather than the boundary when they take a picture. To improve detection performance and speed that are important factors of face detection task, this paper proposes a face detection method that takes spatial context information into consideration. Experiments were performed to verify the usefulness of the proposed method and results indicate that the proposed face detection method can efficiently reduce the false positive rate as well as the runtime of face detection.

• The KIPS Transactions:PartB
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• v.17B no.6
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• pp.405-412
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• 2010

Previous background generation techniques showed bad performance in complex environments since they used only temporal contexts. To overcome this problem, in this paper, we propose a new background generation method which incorporates spatial as well as temporal contexts of the image. This enabled us to obtain 'clean' background image with no moving objects. In our proposed method, first we divided the sampled frame into m*n blocks in the video sequence and classified each block as either static or non-static. For blocks which are classified as non-static, we used MRF framework to model them in temporal and spatial contexts. MRF framework provides a convenient and consistent way of modeling context-dependent entities such as image pixels and correlated features. Experimental results show that our proposed method is more efficient than the traditional one.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.97-100
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• 2007

In order to overcome many defects in the current JPEG standard of still image compression, the new JPEG2000 standard has been development. The JPEG2000 standard is based on the principles of DWT and EBCOT Entropy Coding. EBCOT(Embedded block coding with optimized truncation) is the most important technology in the latest image-coding standard, JPEG2000. However, EBCOT occupies the highest computation time to operate bit-level processing. Therefore, many researches have achieved methods to minimize computation speed of EBCOT. Thus, this paper proposes the method of context-extraction that improves computational architecture. This paper proposes efficient context coding method. The proposed algorithm would apply to hard-wired JPEG2000 Encoder that is used for compression of high resolution image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.12
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• pp.2714-2726
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• 1997

In this paper, adaptive symbol changes-based medical image compression method is presented. First, the differenctial image domain is obtained using the differentiation rules or obaptive predictors applied to original mdeical image. Also, the algorithm determines the context associated with the differential image from the domain. Then prediction symbols which are thought tobe the most probable differential image values are maintained at a high value through the adaptive symbol changes procedure based on estimates of the symbols with polarity coincidence between the differential image values to be coded under to context and differential image values in the model template. At the coding step, the differential image values are encoded as "predicted" or "non-predicted" by the binary adaptive arithmetic encoder, where a binary decision tree is employed. The simlation results indicate that the prediction hit ratios of differential image values using the proposed algorithm improve the coding gain by 25% and 23% than arithmetic coder with ISO JPEG lossless predictor and arithmetic coder with differentiation rules or adaptive predictors, respectively. It can be used in compression part of medical PACS because the proposed method allows the encoder be directly applied to the full bit-planes medical image without a decomposition of the full bit-plane into a series of binary bit-planes as well as lower complexity of encoder through using an additions when sub-dividing recursively unit intervals.

• Investigative Magnetic Resonance Imaging
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• v.3 no.2
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• pp.179-187
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• 1999

Purpose : This paper introduces a computationally inexpensive context-dependent classification of multi-echo MRI with Bayes compound decision model. In order to produce accurate region segmentation especially in homogeneous area and along boundaries of the regions, we propose a classification method that uses contextual information of local enighborhood system in the image. Material and Methods : The performance of the context free classifier over a statistically heterogeneous image can be improved if the local stationary regions in the image are disassociated from each other through the mechanism of the interaction parameters defined at he local neighborhood level. In order to improve the classification accuracy, we use the contextual information which resolves ambiguities in the class assignment of a pattern based on the labels of the neighboring patterns in classifying the image. Since the data immediately surrounding a given pixel is intimately associated with this given pixel., then if the true nature of the surrounding pixel is known this can be used to extract the true nature of the given pixel. The proposed context-dependent compound decision model uses the compound Bayes decision rule with the contextual information. As for the contextual information in the model, the directional transition probabilities estimated from the local neighborhood system are used for the interaction parameters. Results : The context-dependent classification paradigm with compound Bayesian model for multi-echo MR images is developed. Compared to context free classification which does not consider contextual information, context-dependent classifier show improved classification results especially in homogeneous and along boundaries of regions since contextual information is used during the classification. Conclusion : We introduce a new paradigm to classify multi-echo MRI using clustering analysis and Bayesian compound decision model to improve the classification results.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1250-1260
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• 2020

This study proposes a novel deep neural network model that can accurately detect objects and their relationships in an image and represent them as a scene graph. The proposed model utilizes several multimodal features, including linguistic features and visual context features, to accurately detect objects and relationships. In addition, in the proposed model, context features are embedded using graph neural networks to depict the dependencies between two related objects in the context feature vector. This study demonstrates the effectiveness of the proposed model through comparative experiments using the Visual Genome benchmark dataset.

• Culinary science and hospitality research
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• v.20 no.5
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• pp.93-100
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• 2014

This study performed to identify the relationships among experiential value, brand image, satisfaction and customer loyalty in context of full-service restaurant, and to find the moderating effect of gender on the formulated model. SPSS 18.0 and AMOS 18.0 were employed to conduct frequency analysis, reliability analysis, exploratory and confirmatory factor analysis, and multigroup analysis to examine moderating effect. Results confirmed the validity and reliability and found significant relationships among the constructs. First, two factors of experiential value (e.g., aesthetic and economic value) have positive influence on brand image, satisfaction, and brand image was significant predictor of customer satisfaction. Second, satisfaction was significant antecedent of attitudinal loyalty and the attitudinal loyalty has influence on behavioral loyalty. In addition, current study identified moderating effect of gender between playfulness and brand image even though there was on significant relationship between both constructs. These results will be meaningful for developing marketing strategies and successful business especially for full-service restaurants.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.496-500
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• 2009

In EBCOT, the context modeling process takes excessive calculation time and this paper proposed a method to reduce this calculation time. That is, if the finest resolution coefficient is less than a pre-defined transfer factor the coefficient and its descendents skip the context modeling process. There is a trade-off relationship between the calculation time and the image quality or the amount of output data such that as this threshold value increases, the calculation time and the amount of output data decreases, but the image degradation increases. The experimental results showed that in this range the resulting reduction rate in calculation time was from 3% to 64% in average, the reduction rate in output data was from 32% to 73% in average.