• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.774-784
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• 2021

The object detection and recognition process is a very important task in the field of computer vision, and related research is actively being conducted. However, in the actual object recognition process, the recognition accuracy is often degraded due to the resolution mismatch between the training image data and the test image data. To solve this problem, in this paper, we designed and developed an integrated object recognition and super-resolution framework by proposing an image super-resolution technique to improve object recognition accuracy. In detail, 11,231 license plate training images were built by ourselves through web-crawling and artificial-data-generation, and the image super-resolution artificial neural network was trained by defining an objective function to be robust to the image flip. To verify the performance of the proposed algorithm, we experimented with the trained image super-resolution and recognition on 1,999 test images, and it was confirmed that the proposed super-resolution technique has the effect of improving the accuracy of character recognition.

• Journal of Korea Multimedia Society
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• v.22 no.11
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• pp.1269-1279
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• 2019

In medical image analysis, segmentation is considered as a vital process since it partitions an image into coherent parts and extracts interesting objects from the image. In this paper, we consider automatic segmentations of OCT retinal images to find six layer boundaries using convolutional neural networks. Segmenting retinal images by layer boundaries is very important in diagnosing and predicting progress of eye diseases including diabetic retinopathy, glaucoma, and AMD (age-related macular degeneration). We applied well-known CNN architecture for general image segmentation, called Segnet, U-net, and CNN-S into this problem. We also proposed a shortest path-based algorithm for finding the layer boundaries from the outputs of Segnet and U-net. We analysed their performance on public OCT image data set. The experimental results show that the Segnet combined with the proposed shortest path-based boundary finding algorithm outperforms other two networks.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1684-1688
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• 2005

In this paper, authentication technologies for X-ray inspection images in container merchandises are introduced and a method of authentication for X-ray inspection images is proposed. Until now, X-ray images of container merchandises have been managed without any authentication of inspection results and environments, it means that there was no any action for protection of illegal copy and counterfeiting of X-ray images from inspection results. Here, authentication identifies that who did inspect container X-ray images and, whether the container X-ray images were counterfeited or not. Our proposed algorithm indicates to put important information about X-ray inspection results on an X-ray image without affecting quality of the original image. Therefore, this paper will be useful in determining an appropriate technology and system specification for authentication of X-ray inspection images. As a result of experiment, we find that the information can be embedded to X-ray image without large degradation of image quality. Our proposed algorithm has high detection ratio by Quality 20 of JPEG attack.

• Journal of Ocean Engineering and Technology
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• v.24 no.1
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• pp.47-52
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• 2010

This study presents a modified scheme for the radar image simulation of sea waves. A simulated radar image was obtained by taking into account the dot product of the directed vector from the radar and the normal vector of the sea surface. Moreover, to calculate the radar image, we used the radar received power and radar cross section. To demonstrate the effectiveness of the proposed scheme, the wave spectrum from field data was utilized to obtain the simulated sea waves. The radar image was simulated using numerically generated sea waves. The wave statistics from the simulation agrees comparatively with those of the original field data acquired by real radar measurements.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.1617-1620
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• 2008

The effects of the temporal and permanent bright image stickings were examined under variable panel working gas pressure in the 42-in. ac-PDP with a high Xe (11 %) content. In the cells with and without temporal and permanent bright image stickings, the display luminance, firing voltage, and Vt closed curve were measured relative to the working gas pressure. With a decrease in the working gas pressure, the temporal bright image sticking was observed to be reduced, whereas the permanent bright image sticking was observed to be deteriorated.

• Journal of Biosystems Engineering
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• v.40 no.1
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• pp.89-93
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• 2015

Purpose: Machine vision-based image processing methods can be useful for estimating the fresh weight of plants. This study analyzes the ability of two different image processing methods, i.e., morphological and pixel-value analysis methods, to measure the fresh weight of lettuce grown in a closed hydroponic system. Methods: Polynomial calibration models are developed to relate the number of pixels in images of leaf areas determined by the image processing methods to actual fresh weights of lettuce measured with a digital scale. The study analyzes the ability of the machine vision- based calibration models to predict the fresh weights of lettuce. Results: The coefficients of determination (> 0.93) and standard error of prediction (SEP) values (< 5 g) generated by the two developed models imply that the image processing methods could accurately estimate the fresh weight of each lettuce plant during its growing stage. Conclusions: The results demonstrate that the growing status of a lettuce plant can be estimated using leaf images and regression equations. This shows that a machine vision system installed on a plant growing bed can potentially be used to determine optimal harvest timings for efficient plant growth management.

• Journal of Korea Multimedia Society
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• v.17 no.10
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• pp.1171-1181
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• 2014

In this paper, we propose improved methods which are image conversion and extraction method of watershed seed using morphological characteristic of teeth on complement image. Conventional tooth segmentation methods are occurred low detection ratio at molar region and over, overlap segmentation owing to specular reflection and morphological feature of molars. Therefore, in order to solve the problems of the conventional methods, we propose the image conversion method and improved extraction method of watershed seed. First, the image conversion method is performed using RGB, HSI space of tooth image for to extract boundary and seed of watershed efficiently. Second, watershed seed is reconstructed using morphological characteristic of teeth. Last, individual tooth segmentation is performed using proposed seed of watershed by watershed algorithm. Therefore, as a result of comparison with marker controlled watershed algorithm and the proposed method, we confirmed higher detection ratio and accuracy than marker controlled watershed algorithm.

• East Asian Journal of Business Economics (EAJBE)
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• v.9 no.3
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• pp.115-124
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• 2021

Purpose - An empirical analysis of various opinions of experts to build Busan's global city image. Based on this, we provide strategy establishment metrics using opportunities, strengths, and threats to build Busan's global city image. Research design, data and methodology - SWOT-AHP analysis are used in terms of methodology, and this study is based on experts' reviews and answers. In addition, AHP analysis is performed based on SWOT analysis to derive the result values for important priority factors. Result - As a result of the prioritization of SWOT-AHP results, a matrix of strategic development directions for Busan city brand building can be presented. As a result of the composite weighting, the factors related to opportunity were ranked as important. In addition, matrices on SO strategy, ST strategy, WO strategy, and WT strategy were derived. Conclusion - This study is an interdisciplinary study from the economic aspect, international management and international marketing aspect, administrative aspect, and architectural engineering aspect. Through this, the image of a global city of Busan that can overcome COVID-19 and cope with the 4th industry in the future will be built, and Busan will be able to build a global international city image by commercially attracting the 2030 World Expo.

• Current Optics and Photonics
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• v.5 no.6
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• pp.699-710
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• 2021

In this study, we propose a biomimetic optical structure design methodology for investigating micro-optical mechanisms associated with the compound eyes of insects. With these compound eyes, insects can respond fast while maintaining a wide field of view. Also, considerable research attention has been focused on the insect compound eyes to utilize these benefits. However, their nano micro-structures are complex and challenging to demonstrate in real applications. An effectively integrated design methodology is required considering the manufacturing difficulty. We show that photorealistic ray-traced visualization is an effective method for designing the biomimetic of a micro-compound eye of an insect. We analyze the image formation mechanism and create a three-dimensional computer-aided design model. Then, a ray-trace visualization is applied to observe the optical image formation. Finally, the segmented images are stitched together to generate an image with a wide-angle; the image is assessed for quality. The high structural similarity index (SSIM) value (approximately 0.84 to 0.89) of the stitched image proves that the proposed MATLAB-based image stitching algorithm performs effectively and comparably to the commercial software. The results may be employed for the understanding, researching, and design of advanced optical systems based on biological eyes and for other industrial applications.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.2
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• pp.118-124
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• 2022

Marine environment analysis and ship motion prediction during ship navigation are important technologies for safe and economical operation of autonomous ships. As a marine environment analysis technology, there is a method of analyzing waves by measuring the sea states through images acquired based on radar(radio detection and ranging) signal. However, in the process of deriving marine environment information from radar images, noises generated by external factors are included, limiting the interpretation of the marine environment. Therefore, image processing for noise removal is required. In this study, image inpainting by partial convolutional neural network model is proposed as a method to remove noises and reconstruct radar images.