• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1183-1195
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• 2020

Visual saliency detection is an essential task because it is an important part of various vision-based applications. There are many techniques for saliency detection in color images. However, the number of methods for saliency detection in infrared images is limited. In this paper, we introduce a simple approach for saliency detection in infrared images based on the thresholding technique. The input image is thresholded into several Boolean maps, and an initial saliency map is calculated as a weighted sum of the created Boolean maps. The initial map is further refined by using thresholding, morphology operation, and a Gaussian filter to produce the final, high-quality saliency map. The experiment showed that the proposed method has high performance when applied to real-life data.

• Journal of Biosystems Engineering
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• v.22 no.2
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• pp.217-226
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• 1997

This study was to develop a machine vision system to detect and to discriminate 5 kinds of apple surface defectbruise, decay. fleck, worm hole and scar. To detect the defects from an image of apple, thresholding technique was applied to images on various frames (R, G, B, H, S and I) of the color machine vision and an image of near infrared (NIR). To discriminate the detected region of defect, various features of the 5 kind defect regions were extracted from the 4 kinds of images selected above. The features were size of area, roundness, axes length ratio, mean and valiance of pixel values, standard deviation of real part of amplitude spectrum in frequency domain obtained by Fourier transform of pixel data and mean and standard deviation of power spectrum obtained by the same transform of pixel data. Routines to discriminate the defects from the features of image were developed and tested to prove their validity. The test resulted that I-frame and NIR images were the most desirable. Accuracies of the two images to discriminate the defects were noted as 76% and 77%, respectively.

• Journal of Digital Contents Society
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• v.6 no.4
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• pp.255-260
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• 2005

Images such as photos, film and documents can be difficult to interpret because of aging or noise distortion. There are various methods for restoring noise-distorted images using filters and thresholds. Regardless of the condition or type of image, the process is difficult. In this paper we propose a method of digital image processing that we developed in which a composite image is formed by blending and color mapping.

• Proceedings of the Korean Institute of Interior Design Conference
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• 2005.05a
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• pp.110-115
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• 2005

Show window display is a technique of arranging goods for sales promotion, namely, motivating and inducing customers to purchase products. It is not simply exhibiting articles but a technical expression of values retained in exhibited articles and an integrated visual art comprehending color, lighting effect, the customers' angle of vision, differentiation from neighboring stores, harmony with properties, assistive roles of relevant goods, and entire messages provided by these elements. Show window display plays the role of a medium that expresses brand images and attracts consumers. Through the medium, the company's brand image is recognized and the recognition determines the trend of brand sales. Brand images planted to consumers seldom change, and wrong recognition affects not only the brand image but also the company image. The present study purposed to suggest show window display employing brand images different from traditional show window display, to examine the effects of brand images on consumers' intention to purchase, and to propose display design.

• Annual Conference of KIPS
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• 2019.05a
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• pp.615-618
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• 2019

Visual saliency detection is an important part in various vision-based applications. There are a myriad of techniques for saliency detection in color images. However, the number of methods for saliency detection in infrared images is inadequate. In this paper, we introduce a simple approach for pedestrian identification in infrared images using saliency. The input image is thresholded into several Boolean maps, an initial saliency map is then calculated as a weighted sum of created Boolean maps. The initial map is further refined by using thresholding, morphology operation, and Gaussian filter to produce the final, high-quality saliency map. The experiment showed that the proposed method produced high performance results when applied to real-life data.

• Journal of the Optical Society of Korea
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• v.5 no.2
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• pp.43-48
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• 2001

A three-dimensional (3D) display system based on computer-generated integral photography (CGIP) is proposed and its feasibility is discussed. Instead of the pickup process in conventional If, the elemental images of imaginary objects are computer-generated. Using these images, we observed autostereoscopic 3D images in full color and full parallax. The lateral and depth resolutions of the integrated images are limited by some factors such as the image position, object thickness, the lens width, and the pixel size of display panel.

• Journal of the Optical Society of Korea
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• v.5 no.3
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• pp.117-122
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• 2001

A three-dimensional (3D) display system based on computer-generated integral photography (CGIP) is proposed and its feasibility is discussed. Instead of the pickup process in conventional IP, the elemental images of imaginary objects are computer-generated. Using these images, we observed autostereoscopic 3D images in full color and full parallax. The lateral and depth resolutions of the integrated images are limited by some factors such as the image position, object thickness, the lens width, and the pixel size of display panel.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3186-3203
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• 2021

In this paper, a multi-scale local difference directional number (MLDDN) pattern is proposed for pig identification. Firstly, the color images of individual pig are converted into grey images by the most significant bits (MSB) quantization, which makes the grey values have better discrimination. Then, Gabor amplitude and phase responses on different scales are obtained by convoluting the grey images with Gabor masks. Next, by calculating the main difference of local edge directions instead of traditionally edge information, the directional numbers of Gabor amplitude and phase responses are encoded. Finally, the block histograms of the encoded images are concatenated on each scale, and the maximum pooling is adopted on different scales to avoid the high feature dimension. Experimental results on two pigsties show that MLDDN impressively outperforms the other widely used local descriptors.

• International Journal of Advanced Culture Technology
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• v.8 no.4
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• pp.229-234
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• 2020

Dehazing significantly improves image quality by restoring the loss of contrast and color saturation for images taken in the presence. However, when applied to images not taken according to the prior information, dehazing can cause unintended degradation of image quality. To avoid unintended degradations, we present a hazy scene detection algorithm using a single image based on the distributions of hue, saturation, and dark channel. Through a heuristic approach, we find out statistical characteristics of the distribution of hue, saturation, and dark channels in the hazy scene and make a detection model using them. The proposed method can precede the dehazing to prevent unintended degradation. The detection performance evaluated with a set of test images shows a high hit rate with a low false alarm ratio. Ultimately the proposed method can be used to control the effect of dehazing so that the dehazing can be applied to wide variety of images without unintended degradation of image quality.

• Journal of architectural history
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• v.30 no.1
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• pp.33-42
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• 2021

This paper analysed the architectural images on Pleasant Gathering of Leeum, Samsung museum of art, which has been assumed as a work of the Koryo dynasty. Through the comparison between the unique wooden structure at roof edge on the building images and real architectures, it found the buildings on the painting were from China Fujian(福建), not from Korea. It also analysed the color painting on buildings, trees, themes from previous famous paintings and dresses to confirm these images were came from the early period of the Ming dynasty. It is a very unique painting containing various information on the Fujian ancient architecture, but its architecture drawing is not as skillful as typical ancient Chinese paintings.