• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.450-453
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• 2002

In radiotherapy treatment planning, it is critical to deliver the radiation dose to tumor and protect surrounding normal tissue. Recent developments in functional imaging and radiotherapy treatment technology have been raising chances to control tumor saving normal tissues. A brain phantom which could be used for image registration technique of CT-MR and CT-SPECT images using surface matching was developed. The brain phantom was specially designed to obtain imaging dataset of CT, MR, and SPECT. The phantom had an external frame with 4 N-shaped pipes filled with acryl rods, Pb rods for CT, MR, and SPECT imaging, respectively. 8 acrylic pipes were inserted into the empty space of the brain phantom to be imaged for geometric evaluation of the matching. For an optimization algorithm of image registration, we used Downhill simplex algorithm suggested as a fast surface matching algorithm. Accuracy of image fusion was assessed by the comparison between the center points of the section of N-shaped bars in the external frame and the inserted pipes of the phantom and minimized cost functions of the optimization algorithm. Technique with partially transparent, mixed images using color on gray was used for visual assessment of the image registration process. The errors of image registration of CT-MR and CT-SPECT were within 2mm and 4mm, respectively. Since these errors were considered within a reasonable margin from the phantom study, the phantom is expected to be used for conventional image registration between multimodal image datasets..

• Journal of the Korea Fashion and Costume Design Association
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• v.25 no.3
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• pp.1-16
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• 2023

The purposes of this study were to investigate bag purchasing behaviors and design preferences of male and female adult consumers, and to find the differences depending on sex and age variable. A survey was conducted on 400 male and female adults from 20s to 50s. The questionnaire consisted of bag purchase behaviors, bag design preferences, and the subjects' demographic characteristics. The data were analyzed by Cronbach's α, factor analysis, x² test and t-test using SPSS. The results were as follows. First, as bag selection criteria, four factors (practicality, symbolism, aesthetics, and economics) were derived, and adult consumers considered economics as the most important among the factors. As for purchasing information sources, three factors (media, human resources, and store) were derived, and adult consumers considered human resources and store information sources more important than media. The main motive for purchasing bags was age and damage of the owned products, and Internet shopping malls were the most common purchasing place. The average annual cost of purchasing bags was 100,000 to 300,000 won, and the frequency of purchase was about once a year. Second, as bag preference images, four factors (individual, romantic, active, and classic image) were derived, and adult consumers preferred classic images the most. The shoulder bag was the most preferred as the bag shape, and black was the most preferred bag color. For the material, natural leather was the most preferred, and for the size, medium size was the most preferred. Third, bag purchasing behaviors and design preferences showed many significant differences according to the sex and age of the consumers. Therefore, the results of this study suggests that bag companies need to establish product development and marketing strategies in consideration of differences according to the sex and age group of adult consumers.

• Journal of the Korean Society of Radiology
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• v.83 no.6
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• pp.1240-1258
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• 2022

The lymphatic system provides a route for the spread of inflammation and malignancies. The identification of nodal stations and lymphatic pathways of tumor spread is important for tumor staging, choice of therapy, and the prediction of the prognosis of patients with malignant diseases. Because lymph node metastasis is common in primary intra-abdominal malignant tumors, its detection is essential for radiologists to understand the pattern of disease spread. Using schematic pictures and color-coded CT images, this pictorial essay describes the locations and nomenclature of the abdominal lymph nodes. Furthermore, the lymphatic drainage pathways of the upper and lower gastrointestinal tracts, liver, gallbladder, bile duct, and pancreas have been highlighted. In addition, lymph nodes belonging to the regional lymph nodes in malignant tumors arising from each organ are described, and certain cases are presented with images from patients.

• Journal of IKEEE
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• v.28 no.1
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• pp.65-71
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• 2024

This paper proposes a neural network that can reduce the number of parameters while reducing matching errors in occluded regions to increase the accuracy of depth maps in stereo matching. Stereo matching-based object recognition is utilized in many fields to more accurately recognize situations using images. When there are many objects in a complex image, an occluded area is generated due to overlap between objects and occlusion by background, thereby lowering the accuracy of the depth map. To solve this problem, existing research methods that create context information and combine it with the cost volume or RoIselect in the occluded area increase the complexity of neural networks, making it difficult to learn and expensive to implement. In this paper, we create a depthwise seperable neural network that enhances regional feature extraction before cost volume generation, reducing the number of parameters and proposing a neural network that is robust to occlusion errors. Compared to PSMNet, the proposed neural network reduced the number of parameters by 30%, improving 5.3% in color error and 3.6% in test loss.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.95-103
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• 2024

This study examines the works of Yohji Yamamoto, one of the most influential fashion designers in 21st century Japan. The research focuses on the Yohji Yamamoto Women Ready To Wear collections showcased at Paris Fashion Week (2019F/W-2024S/S). The research methodology includes case analysis and summarization of images. The study analyzes the Yohji Yamamoto brand development and design style. A total of 399 runway images from 2019F/W-2024S/S were downloaded from VOGUE and analyzed based on four aspects: silhouette, color, material, and item. The analysis of these aspects reveals the aesthetic characteristics of Yohji Yamamoto: Zen-like, simplicity, naturalness, and elegance. The findings indicate that these aesthetic ideas are the core elements of Yohji Yamamoto's unique aesthetic and play a significant role in shaping the brand's style.

• Clinical Endoscopy
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• v.55 no.1
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• pp.113-121
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• 2022

Background/Aims: We have been developing artificial intelligence based polyp histology prediction (AIPHP) method to classify Narrow Band Imaging (NBI) magnifying colonoscopy images to predict the hyperplastic or neoplastic histology of polyps. Our aim was to analyze the accuracy of AIPHP and narrow-band imaging international colorectal endoscopic (NICE) classification based histology predictions and also to compare the results of the two methods. Methods: We studied 373 colorectal polyp samples taken by polypectomy from 279 patients. The documented NBI still images were analyzed by the AIPHP method and by the NICE classification parallel. The AIPHP software was created by machine learning method. The software measures five geometrical and color features on the endoscopic image. Results: The accuracy of AIPHP was 86.6% (323/373) in total of polyps. We compared the AIPHP accuracy results for diminutive and non-diminutive polyps (82.1% vs. 92.2%; p=0.0032). The accuracy of the hyperplastic histology prediction was significantly better by NICE compared to AIPHP method both in the diminutive polyps (n=207) (95.2% vs. 82.1%) (p<0.001) and also in all evaluated polyps (n=373) (97.1% vs. 86.6%) (p<0.001) Conclusions: Our artificial intelligence based polyp histology prediction software could predict histology with high accuracy only in the large size polyp subgroup.

• Science of Emotion and Sensibility
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• v.12 no.3
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• pp.307-316
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• 2009

The basic objective of this study is to suggest the city image ideas and methods of application based on the analysis of the regional characteristics and image factors in making proposal for integrated design for public facilities. Through understanding and analyzing natural, environmental, industrial characteristics, the city was subdivided into urban, marine, inland, and industrial complex areas. Also, local residents' attitude survey and the city's cultural iconic image survey analysis was performed simultaneously, and the survey results were used to establish the strategy for Pohang's city design identity and were applied in public facility design development process. Developing from the identity motive, "texture", the images of "iron", "marine", "science" were selected as core image of identity and were applied as design factors. Four unique colors were selected for each areas based on scenery color analysis. For facilities that needed to be installed separately in all four areas, "application of color and material consistency" and "application of shape consistency and partial color diversity consistency" were suggested to integrate the image of the city as a whole through establishing distinctive image for each area.

• Journal of Advanced Navigation Technology
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• v.9 no.1
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• pp.48-55
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• 2005

In this paper, we propose an efficient moving object tracking technique for multi-camera surveillance system. Color CCD cameras used in this system are network cameras with their own IP addresses. Input image is transmitted to the media server through wireless connection among server, bridge, and Access Point (AP). The tracking system sends the received images through the network to the tracking module, and it tracks moving objects in real-time using color matching method. We compose two sets of cameras, and when the object is out of field of view (FOV), we accomplish hand-over to be able to continue tracking the object. When hand-over is performed, we use MHI(Motion History Information) based on color information and M-bin histogram for an exact tracking. By utilizing MHI, we can calculate direction and velocity of the object, and those information helps to predict next location of the object. Therefore, we obtain a better result in speed and stability than using template matching based on only M-bin histogram, and we verified this result by an experiment.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.12
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• pp.889-898
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• 2013

Due to the popularization of high-performance capturing equipments and the emergence of powerful image-editing softwares, it is easy to make high-quality counterfeit money. However, the probability of detecting counterfeit money to the general public is extremely low and the detection device is expensive. In this paper, a counterfeit money detection algorithm using a general purpose scanner and computer system is proposed. First, the printing features of color printers are calculated using morphological operations and gray-level co-occurrence matrix. Then, these features are used to train a support vector machine classifier. This trained classifier is applied for identifying either original or counterfeit money. In the experiment, we measured the detection rate between the original and counterfeit money. Also, the printing source was identified. The proposed algorithm was compared with the algorithm using wiener filter to identify color printing source. The accuracy for identifying counterfeit money was 91.92%. The accuracy for identifying the printing source was over 94.5%. The results support that the proposed algorithm performs better than previous researches.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.4
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• pp.68-74
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• 2017

This paper presents a joint demosaicking and arbitrary-ratio down sampling algorithm for color filter array (CFA) images. Color demosaiking is a necessary part of image signal processing pipeline for many types of digital image recording system using single sensor. Also, such as smart phone, obtained high resolution image from image sensor has to be down-sampled to be displayed on the screen. The conventional solution is "Demosaicking first and down sampling later". However, this scheme requires a significant amount of memory and computational cost. Also, artifacts can be introduced or details get damaged during demosaicking and down sampling process. In this paper, we propose a method in which demosaicking and down sampling are working simultaneously. We use inverse mapping of Bayer CFA and then joint demosaicking and down sampling with arbitrary-ratio scheme based on signal decomposition of high and low frequency component in input data. Experimental results show that our proposed algorithm has better image quality performance and much less computational cost than those of conventional solution.