• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.339-340
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• 2007

Face detection plays an important role in HCI and face recognition. In this paper, we propose a rotation-invariant real-time face detection algorithm for color images in complex background. It consists of four processing step: (1) motion detection, (2) skin color region filler, (3) Eyemap detector for rotated face, and (4) Adaboost face classifier. This system has been tested in in-door environments, such as office and achieves over 95% detection rate.

• Journal of Korea Multimedia Society
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• v.11 no.12
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• pp.1668-1675
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• 2008

In this paper, we propose a post-processing technique developed for the subjective improvement of color resolution in DCT-coded color images. The high frequency components caused by complex object parts are compressed and impaired through DCT-based image processing, so color distortions such as blurs in high saturated regions are observed. It's mainly due to the severe loss of color data as Cb and Cr. Generally, the activities of chroma elements in DCT domain correlate strongly with that of luminance as spatial frequency gets higher, and based on the relations between chroma and luma AC activities, we compensate destructed Cb, Cr coefficients using modifications from Y coefficients. Simulation results show that the proposed method enhances color resolution in high saturated region, and improves the visual quality.

• Korean Journal of Remote Sensing
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• v.11 no.2
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• pp.43-57
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• 1995

This paper presents reconstruction of disparity in images. To achieve this, the algorithm was made up of two different procedures - one is extraction of boundaries for man-made structures and the other is matching of the structures. In the extraction of boundaries for man-made structures, we assume that man-made structures are composed of lines and the lines make up closed polygon. The convertional algorithms of the edges extraction may not perceive man-made structures and have problems that matching algorithms were too complex. This paper proposed sub-pixel boundaries extraction algorithm that fused split-and-merge and image improvement algorithms to overcome complexity. In matching procedure, feature-based algorithm that minimize the proposed cost function are used and the cost fuction considers movement of mid-points for left and right images to match structures. Because we could not obtain disparity of inner parts for the man-made structures, interpolation method was used. The experiment showed good results.

• Cross-Cultural Studies
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• v.25
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• pp.131-158
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• 2011

In the Sakha(Yakutia) Republic, culture and politics continue to be interwined. Shamanism recently has come out of hiding after Soviet repression, and into fashion. Images of the shaman are changing in villages, where traditional healers have maintained their practices in difficult conditions, and in cities, where a resurgence of spirit belief and healing has led to the revitalization of their nationalism. Shamans and folk healers manipulate their own images, and in turn are changed by the upheavals of politicized cultural revitalization. In this complex and interactive context, folklore about traditional shamans has become especially rich and accessible. I argue here that religion has become an idiom through which competing definitions of homeland and national pride are being shaped. Until September 2002, Yakutsk had never had a 'temple' devoted to the practice of traditional shamanic beliefs. Indeed the whole concept that a building 'Archie Jiete' could contain or represent the beliefs, values and rituals of the Sakha people was new, and highly controversial.

• Journal of the Optical Society of Korea
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• v.12 no.4
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• pp.275-280
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• 2008

We propose a method generating elemental images for the integral imaging using 4-step phaseshifting digital holography. Phase shifting digital holography is a way recording the digital hologram by changing the phase of the reference beam and extracting the complex field of the object beam. Since all 3D information is captured by phase-shifting digital holography, the elemental images for any specifications of the lens array can be generated from single phase-shifting digital holography. In experiment, phase-shifting is achieved by rotating half- and quarter- wave plates and the resultant interference patterns are captured by a $3272{\times}2469$ pixel CCD camera with $27{\mu}m{\times}27{\mu}m$ pixel size.

• Journal of the Korean Physical Society
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• v.73 no.12
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• pp.1845-1848
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• 2018

We introduce a process for optically reconstructing full-color holographic images recorded by optical scanning holography. A complex RGB-color hologram was recorded and converted into a binary hologram using a direct binary search (DBS) algorithm. The generated binary hologram was then optically reconstructed using a spatial light modulator. The discrepancies between the reconstructed object sizes and colors due to chromatic aberration were corrected by adjusting the reconstruction parameters in the DBS algorithm. To the best of our knowledge, this represents the first optical reconstruction of a full-color hologram recorded by optical scanning holography.

• Journal of Institute of Convergence Technology
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• v.11 no.1
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• pp.1-5
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• 2021

Deep learning based methods achieve state-of-the-art accuracy, however, they typically rely on supervised training with large labeled datasets. It is known in many medical applications that labeling medical images requires significant expertise and much time, and typical hand-tuned approaches for data augmentation fail to capture the complex variations in such images. This paper proposes a 3D image augmentation method to overcome these difficulties. It allows us to enrich diversity of training data samples that is essential in medical image segmentation tasks, thus reducing the data overfitting problem caused by the fact the scale of medical image dataset is typically smaller. Our numerical experiments demonstrate that the proposed approach provides significant improvements over state-of-the-art methods for 3D medical image segmentation.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.27 no.1
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• pp.37-55
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• 2023

In this paper we propose a new algorithm for detecting and counting flowers in a complex background based on digital images. The algorithm mainly includes the following parts: edge contour extraction of flowers, edge contour determination of overlapped flowers and flower counting. We use a contour detection technique in Computer Vision (CV) to extract the edge contours of flowers and propose an improved algorithm with a concave point detection technique to find accurate segmentation for overlapped flowers. In this process, we first use the polygon approximation to smooth edge contours and then adopt the second-order central moments to fit ellipse contours to determine whether edge contours overlap. To obtain accurate segmentation points, we calculate the curvature of each pixel point on the edge contours with an improved Curvature Scale Space (CSS) corner detector. Finally, we successively give three adaptive judgment criteria to detect and count flowers accurately and automatically. Both experimental results and the proposed evaluation indicators reveal that the proposed algorithm is more efficient for flower counting.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.166-171
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• 2023

With significant advancements in the field of artificial intelligence, many novel algorithms and technologies have emerged. Currently, AI painting can generate high-quality images based on textual descriptions. However, it is often challenging to control details when generating images, even with complex textual inputs. Therefore, there is a need to implement additional control mechanisms beyond textual descriptions. Based on ControlNet, this passage describes a combined utilization of various local controls (such as edge maps and depth maps) and global control within a single model. It provides a comprehensive exposition of the fundamental concepts of ControlNet, elucidating its theoretical foundation and relevant technological features. Furthermore, combining methods and applications, understanding the technical characteristics involves analyzing distinct advantages and image differences. This further explores insights into the development of image generation patterns.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.88-93
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• 2024

The main problem with existing edge detection techniques is that they have many limitations in detecting edges for complex and diverse images that exist in the real world. This is because only edges of a defined shape are discovered based on an accurate definition of the edge. One of the methods to solve this problem is the cost minimization method. In the cost minimization method, cost elements and cost functions are defined and used. The cost function calculates the cost for the candidate edge model generated according to the candidate edge generation strategy, and if the cost is found to be satisfactory, the candidate edge model becomes the edge for the image. In this study, we proposed an enhanced candidate edge generation strategy to discover edges for more diverse types of images in order to improve the shortcoming of the cost minimization method, which is that it only discovers edges of a defined type. As a result, improved edge detection results were confirmed.