• Journal of Korea Multimedia Society
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• v.22 no.1
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• pp.18-26
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• 2019

In this paper we propose how to detect circular objects in the gray scale image and segment them using the discrete Morse theory, which makes it possible to analyze the topology of a digital image, when it is transformed into the data structure of some combinatorial complex. It is possible to get meaningful information about how many connected components and topologically circular shapes are in the image by computing the persistent homology of the filtration using the Morse complex. We obtain a Morse complex by modeling an image as a cubical cellular complex. Each cell in the Morse complex is the critical point at which the topological structure changes in the filtration consisting of the level sets of the image. In this paper, we implement the proposed algorithm of segmenting the circularly shaped objects with a long persistence of homology as well as computing persistent homology along the filtration of the input image and displaying in the form of a persistence diagram.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.4
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• pp.392-400
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• 2021

Unlike optical equipment, SAR(Synthetic Aperture Radar) has the advantage of obtaining images in all weather, and object detection in SAR images is an important issue. Generally, deep learning-based object detection was mainly performed in real-valued network using only amplitude of SAR image. Since the SAR image is complex data consist of amplitude and phase data, a complex-valued network is required. In this paper, a complex-valued ResNet network is proposed. SAR image object detection was performed by combining the ROI transformer detector specialized for aerial image detection and the proposed complex-valued ResNet. It was confirmed that higher accuracy was obtained in complex-valued network than in existing real-valued network.

• Fashion & Textile Research Journal
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• v.19 no.4
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• pp.365-372
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• 2017

This study systematically identified the influence of the school look fashion image on public culture, which is used for increasingly sexualized marketing appeal by domestic Girl Groups. We examined and analyzed the school look fashion image of Girl Groups, focusing on the Lolita complex which is particularly influential in the sexual appeal of domestic popular fashion. The method of this study is based on a literature review from the years 2007 to 2016, when the female girl groups began to receive attention. The music videos of the female girl groups in the top 100 charts of 'Melon' from 2006 to 2-16, which provides the largest mobile music service in Korea, were watched and analyzed as primary data. As a result, it was found that the 'school fashion look image' of adolescence which was used as costumes for Girl Groups, plays a role in commercializing the image of a 'girl', and the types and characteristics of school look fashion image are drawn in two ways. First, it is the image of a seductive Lolita complex. This is the case where young girls wear school look fashion image to emphasize their sexual maturity. Second, it is the case that is using the school look fashion image in order to perform with the 'young girl' concept, as an image of the enchanting Lolita complex; in addition, the erotic body image is more explicitly exposed through choreography and nakedness.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.5170-5188
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• 2015

This paper proposes a novel progressive secret image-hiding scheme based on the inpainting technique, the vector quantization technique (VQ) and the exploiting modification direction (EMD) technique. The proposed scheme first divides the secret image into non-overlapping blocks and categorizes the blocks into two groups: complex and smooth. The blocks in the complex group are compressed by VQ with PCA sorted codebook to obtain the VQ index table. Instead of embedding the original secret image, the proposed method progressively embeds the VQ index table into the cover images by using the EMD technique. After the receiver recovers the complex parts of the secret image by decoding the VQ index table from the shadow images, the smooth parts can be reconstructed by using the inpainting technique based on the content of the complex parts. The experimental results demonstrate that the proposed scheme not only has the advantage of progressive data hiding, which involves more shadow images joining to recover the secret image so as to produce a higher quality steganography image, but also can achieve high hiding capacity with acceptable recovered image quality.

• Journal of Information Processing Systems
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• v.9 no.3
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• pp.349-364
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• 2013

The big challenge in current content-based image retrieval systems is to reduce the semantic gap between the low level-features and high-level concepts. In this paper, we have proposed a novel framework for efficient image retrieval to improve the retrieval results significantly as a means to addressing this problem. In our proposed method, we first extracted a strong set of image features by using the dual-tree rotated complex wavelet filters (DT-RCWF) and dual tree-complex wavelet transform (DT-CWT) jointly, which obtains features in 12 different directions. Second, we presented a relevance feedback (RF) framework for efficient image retrieval by employing a support vector machine (SVM), which learns the semantic relationship among images using the knowledge, based on the user interaction. Extensive experiments show that there is a significant improvement in retrieval performance with the proposed method using SVMRF compared with the retrieval performance without RF. The proposed method improves retrieval performance from 78.5% to 92.29% on the texture database in terms of retrieval accuracy and from 57.20% to 94.2% on the Corel image database, in terms of precision in a much lower number of iterations.

• Architectural research
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• v.3 no.1
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• pp.21-27
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• 2001

This study addressing the underlying strategies for Andong municipal museum complex development is in timely view that Andong has obtained a worldwide reputation as a treasury of traditional Korean Confucian culture. Thus far, there has been a tendency that various local museums are proposed to meet architectural aspirations architects and users commonly hold. Overall, though, the major role they play in making overall city image has not been considered in a systematic manner. Based on Lee's (2001) two previous studies, this study summarized the utility of cognitive distance and cognitive map concepts, which are proposed by Kevin Lunch (1976) to evaluate city image, in planning Andong municipal museum complex (AMMC). Sample is stratified into city residents and outsiders, and also into the general public and design-related professionals to see if there is any group difference in constructing their mental image. Three major findings are obtained. First, familiarity, so-called the degree of knowing, is the function of the length of stay in a designated area. That is, the longer people stay in Andong, the more likely they are familiar with its overall environmental aspects. Second, mental proximity of Andong municipal museum complex relative to existing cultural landmarks is closely related to the degree of how people value those landmarks in terms of their significance. Dosan Seowon and Hahoe folk village are most highly valued, which means higher proximity. Third, functional diversity turned out to be the most important design dimension, while display mechanism are least valued. Cognitive simulations of this sort are meaningful in that projected composite image might be a rough first approximation of true public image.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.199-202
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• 2003

An effective method is proposed for detecting, acquisition and tracking of a moving object using a disturbance map method in complex image sequences. A significant moving object is detected and tracked within the field of view by computing a modified disturbance map method between an Input image and a temporal average image. This method is very efficient in the serveillance application of digital CCTV and an automatic tracking camera. Experimental results using a real image sequence confirmed that the proposed method can effectively detect and track a significant moving object in complex image sequences.

• Fashion & Textile Research Journal
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• v.11 no.1
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• pp.14-23
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• 2009

This study is to analyze the regional differences of sensibility image of wedding dress design for single women of marriageable age in Ulsan and Seoul. The conclusions of this study were as follows. In silhouette, both of two regions were not significant differences but within the same sensibility image there was a bit of differences. In neckline, reminded sweetheart of pure image, yet those of Ulsan reminded sweetheart of feminine image. Both of two regions reminded V of hard image, boat of feminine image, square of hard image, halter of complex image. But within the same sensibility image there was a bit of differences between two regions. Oval was significant differences between two regions. Subject of Ulsan reminded oval of mature image, yet those of Seoul reminded oval of elegance image. It was reminded ruffle of complex image. Subject of Ulsan reminded china of hard image, yet those of Seoul reminded china of calm image. In material, it was not significant differences between two regions, but within the same sensibility image there was a bit of differences between two regions. In detail, subject of Ulsan reminded ruffle of messy image, yet those of Seoul reminded ruffle of complex image. Both of two areas reminded ribbon of pure image, button of pure image. Subject of Ulsan reminded beads of feminine image, yet those of Seoul reminded beads of pure image. In conclusion, it could be said that there was no major differences in sensibility image for wedding dress design between Ulsan and Seoul.

• Journal of Multimedia Information System
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• v.7 no.1
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• pp.1-10
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• 2020

The image analysis is an important and predominant task for classifying the different parts of the image. The analysis of complex image analysis like histopathological define a crucial factor in oncology due to its ability to help pathologists for interpretation of images and therefore various feature extraction techniques have been evolved from time to time for such analysis. Although deep reinforcement learning is a new and emerging technique but very less effort has been made to compare the deep learning and deep reinforcement learning for image analysis. The paper highlights how both techniques differ in feature extraction from complex images and discusses the potential pros and cons. The use of Convolution Neural Network (CNN) in image segmentation, detection and diagnosis of tumour, feature extraction is important but there are several challenges that need to be overcome before Deep Learning can be applied to digital pathology. The one being is the availability of sufficient training examples for medical image datasets, feature extraction from whole area of the image, ground truth localized annotations, adversarial effects of input representations and extremely large size of the digital pathological slides (in gigabytes).Even though formulating Histopathological Image Analysis (HIA) as Multi Instance Learning (MIL) problem is a remarkable step where histopathological image is divided into high resolution patches to make predictions for the patch and then combining them for overall slide predictions but it suffers from loss of contextual and spatial information. In such cases the deep reinforcement learning techniques can be used to learn feature from the limited data without losing contextual and spatial information.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.498-503
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• 2009

As for Hadamard Transform, because the calculation time of this transform is slower than Discrete Cosine Transform (DCT) and Fast Fourier Transform (FFT), the effectiveness and the practicality are insufficient. Then, the computational complexity can be decreased by using the butterfly operation as well as FFT. We composed calculation time of FFT with that of Fast Complex Hadamard Transform by constructing the algorithm of Fast Complex Hadamard Transform. They are indirect conversions using program of complex number calculation, and immediate calculations. We compared calculation time of them with that of FFT. As a result, the reducing the calculation time of the Complex Hadamard Transform is achieved. As for the computational complexity and calculation time, the result that quadrinomial Fast Complex Hadamard Transform that don't use program of complex number calculation decrease more than FFT was obtained.