• Journal of Ocean Engineering and Technology
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• v.9 no.2
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• pp.75-82
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• 1995

The free surface effects on the aerodynamic performance of 2-D wings are investigated based on the potential flow approximation. The wing is represented b source and vortex distributions on the wing surface. The steady free surface effect is taken into account by source distribution on the free surface and the velocity potentials of air and water flows are obtained. Using three different techniques, namely, positive image method, inverse image method and source distribution method, numerical results are obtained for wave elevation, pressure distribution and lift coefficient with various foil sections. The wave elevation calculated by the inverse image method is shown to be very small even at higher speeds so that the free surface effect on the performance of wings is regraded negligible. However, the wave elevations by the positive image method and source distribution method are relatively high at higher speeds and accordingly the free surface effects on wings can not be neglected.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.3
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• pp.41-48
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• 2012

In this paper, we propose a method of edge detection for noisy image. The proposed method uses a progressive filter for noise reduction and a Sobel operator for edge detection. The progressive filter combines a median filter and a modified rational filter. The proposed method for noise reduction adjusts rational filter direction according to an edge in the image which is obtained by median filtering. Our method effectively attenuates the noise while preserving the image details. Edge detection is performed by a Sobel operator. This operator can be implemented by integer operation and is therefore relatively fast. Our proposed method not only preserves edge, but also reduces noise in uniform region. Thus, edge detection is well performed. Our proposed method could improve results using further developed Sobel operator. Experimental results show that our proposed method has better edge detection with correct positions than those by existing median and rational filtering methods for noisy image.

• Korean Journal of Cognitive Science
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• v.22 no.4
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• pp.347-364
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• 2011

In this paper, we propose a automatic image bases extraction method for visual image reconstruction from brain activity using Non-negative Matrix Factorization (NMF). Image bases are basic elements to construct and present a visual image. Previous method used brain activity that evoked by predefined 361 image bases of four different sizes: $1{\times}1$, $2{\times}1$, $1{\times}2$, $2{\times}2$, and $2{\times}2$. Then the visual stimuli were reconstructed by linear combination of all the results from these image bases. While the previous method used 361 predefined image bases, the proposed method automatically extracts image bases which represent the image data efficiently. From the experiments, we found that the proposed method reconstructs the visual stimuli better than the previous method.

• Journal of Korea Multimedia Society
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• v.22 no.11
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• pp.1223-1232
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• 2019

The injection is the input method of the image feature vector from the encoder to the decoder. Since the image feature vector contains object details such as color and texture, it is essential to generate image captions. However, the bidirectional decoder model using the existing injection method only inputs the image feature vector in the first step, so image feature vectors of the backward sequence are vanishing. This problem makes it difficult to describe the context in detail. Therefore, in this paper, we propose the parallel injection method to improve the description performance of image captions. The proposed Injection method fuses all embeddings and image vectors to preserve the context. Also, We optimize our image caption model with Bidirectional Gated Recurrent Unit (Bi-GRU) to reduce the amount of computation of the decoder. To validate the proposed model, experiments were conducted with a certified image caption dataset, demonstrating excellence in comparison with the latest models using BLEU and METEOR scores. The proposed model improved the BLEU score up to 20.2 points and the METEOR score up to 3.65 points compared to the existing caption model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.270-275
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• 2018

Method for improving the image quality are divided into a tone mapping method and a retinex theory based method. Typical example of the image quality enhancement method using tone mapping method is one using image characteristics like histogram. In this paper, we propose a hardware design of real-time wide dynamic range algorithm based on tone mapping method for image quality enhancement. The proposed method divides the image into the luminance and chroma components and then improves the chroma region based on the variation of the luminance component. Adding to that, it is designed to be compatible with the existing 8-bit signal, using high quality image with 12-bit extended signal according to the desired flow. As a result of simulation, it is confirmed that the image quality is improved, and the hardware design is confirmed that the real-time operations is possible at the maximum frequency at 138.26MHz.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.2
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• pp.90-98
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• 2015

This research propose with image-based visual a new approach to design a feedback control of mobile robot. because mobile robot must be recharged periodically, it is necessary to detect and move to docking station. Generally, laser scanner is used for detect of position of docking station. CCD Camera is also used for this purpose. In case of using camera, the position-based visual servoing method is widely used. But position-based visual servoing method requires the accurate calibration and it is hard and complex work. Another method using cameras is inmage-based visual feedback. Recently, image based visual feedback is widely used for robotic application. But it has a problem that cannot have linear trajectory in the 3-dimensional space. Because of this weak point, image-based visual servoing has a limit for real application. in case of 2-dimensional movement on the plane, it has also similar problem. In order to solve this problem, we point out the main reason of the problem of the resolved rate control method that has been generally used in the image-based visual servoing and we propose an image-based visual feedback method that can reduce the curved trajectory of mobile robot in th cartesian space.

• The Transactions of the Korea Information Processing Society
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• v.3 no.4
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• pp.720-732
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• 1996

Spatial match retrieval methods for iconic image databases recognize an image document as several icon symbols. Therefore the iconic symbols are used as primary keys to index the image document. When a user requires content-based retrieval ofimages, a spatial match retrieval method converts a query image into iconic symbols and then retrieves relevant images by accessing stored images. In order to support content-based image retrieval efficiently, we, in this paper, propose spatial match retrieval methods using signatures for iconic image databases. For this, we design new index representations of two-dimensional iconic images and explain implemented system.. In addition, we compare the conventional 9-DLT and our two-dimensional image retrieval method in terms of retrieval precision and recall ratio. We show that our method is more efficient than the conventional method.

• Journal of the Korea Computer Industry Society
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• v.4 no.4
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• pp.589-598
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• 2003

In the conventional fractal image compression in the DWT(discrete wavelet transform), the domain and range blocks were classified as B${\times}$B block size first before all domain block for each range block was searched. The conventional method has a disadvantages that the encoding time takes too long, since the domain block for entire image was searched. As an enhancement to such inefficiencies and image quality, this paper proposes wavelet-based fractal image compression with multiscale factors. Thus, this proposed method uses multiscale factor along each level and band to enhance an overall image quality. In encoding process of this method, the range blocks are not searched for all the domain blocks; however, using the self affine system the range blocks are selected from the blocks in the upper level. The image qualify of the conventional method is 32.30[dB], and the proposed method is 35.97[dB]. The image quality is increased by 3.67[dB].

• Journal of Korea Multimedia Society
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• v.15 no.10
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• pp.1205-1211
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• 2012

Recently, the evaluating method of the bone mineral density (BMD) in X-ray absorptiometry image has been studied for the early diagnosis of osteoporosis which is known as a metabolic disease. The BMD, in general, is evaluated by calculating pixel intensity in the bone segmented regions. Accurate bone region extraction is extremely crucial for the BMD evaluation. So, a X-Ray image enhancement is needed to get precise bone segmentation. In this paper, we propose an image enhancement method of X-ray image having multiple noise based sparse representation. To evaluate the performance of proposed method, we employ the contrast to noise ratio (CNR) metric and cut-view graphs visualizing image enhancement performance. Experimental results show that the proposed method outperforms the BayesShrink noise reduction methods and the previous noise reduction method in sparse representation with general noise model.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.135-141
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• 2004

Image interpolation is an image enlargement method that calculates an empty pixel value using the information of given pixel values. Since a natural image is composed of various spatial frequency components, it is difficult for one method to interpolate pixels with various spatial frequencies. In this paper, we propose an image interpolation method using multiple neural networks with spatial frequency characteristic. Input image is segmented according to spatial frequency by local variance, and each segmented image is interpolated using neural network established for spatial frequency band. The proposed method is applied to line doubling that becomes an important part in image interpolation because of deinterlacing. In simulation the proposed algorithm shows the improved PSNR result compared with conventional algorithms and method using single neural network.