• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.55-58
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• 2024

In this paper, we propose a design and implementation of big data-based fine dust anomaly detection machine learning system. The proposed is system that classifies the fine dust air quality index through meteorological information composed of fine dust and big data. This system classifies fine dust through the design of an anomaly detection algorithm according to the outliers for each air quality index classification categories based on machine learning. Depth data of the image collected from the camera collects images according to the level of fine dust, and then creates a fine dust visibility mask. And, with a learning-based fingerprinting technique through a mono depth estimation algorithm, the fine dust level is derived by inferring the visibility distance of fine dust collected from the monoscope camera. For experimentation and analysis of this method, after creating learning data by matching the fine dust level data and CCTV image data by region and time, a model is created and tested in a real environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.12C
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• pp.1225-1238
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• 2003

We present an efficient algorithm for skew correction of business card images obtained by a PDA (personal digital assistant) camera. The proposed method is composed of four parts: block adaptive binarization (BAB), stripe generation, skew angle calculation, and image rotation. In the BAB, an input image is binarized block by block so as to lessen the effect of irregular illumination and shadow over the input image. In the stripe generation, character string clusters are generated merging adjacent characters and their strings, and then only clusters useful for skew angle calculation are output as stripes. In the skew angle calculation, the direction angles of the stripes are calculated using their central moments and then the skew angle of the input image is determined averaging the direction angles. In the image rotation, the input image is rotated by the skew angle. Experimental results shows that the proposed method yields skew correction rates of about 93% for test images of several types of business cards acquired by a PDA under various surrounding conditions.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.22 no.2
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• pp.273-282
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• 1992

The purpose of this study was to propose the utility which was evaluated the digital image processing and clinical application of the videodensitomery. The experiments were performed with IBM-PC/16bit-AT compatible, video camera(CCdtr55, Sony Co., Japan), an color monitor(MultiSync 3D, NEC, Japan) providing the resolution of 512×480 and 64 levels of gray. Sylvia Image Capture Board for the ADC(analog to digital converter) was used, composed of digitized image from digital signal and the radiographic density was measured by 256 level of gray. The periapical radiograph(Ektaspeed EP-21, Kodak Co., U. S. A) which was radiographed dried human mandible by exposure condition of 70 kVp and 48 impulses, was used for primary X-ray detector. And them evaluated for digitzed image by low and high pass filtering, correlations between aluminum equivalent values and the thickness of aluminum step wedge, aluminum equivalent values of sound enamel, dentin, and alveolar bone, the range of diffuse density for gray level ranging from 0 to 255. The obtained results were as follows: 1. The edge between aluminum steps of digitized image were somewhat blurred by low pass filtering, but edge enhancement could be resulted by high pass filtering. Expecially, edge enhancement between distal root of lower left 2nd molar and alveolar lamina dura was observed. 2. The correlation between aluminum equivalent values and the thickness of aluminum step wedge was intimated, yielding the coefficient of correlation r=0.9997(p<0.00l), the regression line was described by Y=0.9699X+0.456, and coefficient of variation amounting to 1.5%. 3. The aluminum equivalent values of sound enamel, dentin, and alvolar bone were 15.41㎜, 12.48㎜, 10.35㎜, respectively. 4. The range of diffuse density for gray level ranging from 0 to 255 was wider enough than that of photodenstiometer to be within the range of 1-4.9.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.6
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• pp.413-422
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• 2013

In this paper, we propose a novel method for real-time lane detection that is robust for inclined roads and not require a camera parameter, the Inverse Perspective Transform of the image, and the proposed lane filter. After finding the vanishing point from the start frame of the image and storing the region surrounding the vanishing point as the Template Area(TA), our method predict the lanes by scanning toward the lower part from the vanishing point of the image and obtain the image removed the perspective effect using the Inverse Perspective Transform coefficients extracted based on the predicted lanes. To robustly determine lanes on inclined roads, the region surrounding the vanishing point is set up as the template area (TA), and, by recalculating the vanishing point by tracing the area similar to the TA (SA) in the input image through template matching, it responds to the changes on the road conditions. The proposed method for a more robust lane detection method for inclined roads is a lane detection method by applying a lane detection filter on an image removed of the perspective effect. Through this method, the processing region is reduced and the processing procedure is simplified to produce a satisfactory lane detection result of about 40 frames per second.

• Korean Journal of Agricultural Science
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• v.39 no.3
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• pp.407-412
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• 2012

Soil texture has an important influence on agriculture such as crop selection, movement of nutrient and water, soil electrical conductivity, and crop growth. Conventionally, soil texture has been determined in the laboratory using pipette and hydrometer methods requiring significant amount of time, labor, and cost. Recently, in-situ soil texture classification systems using optical diffuse reflectometry or mechanical resistance have been reported, especially for precision agriculture that needs more data than conventional agriculture. This paper is a part of overall research to develop an in-situ soil texture classification system using image processing. Issues investigated in this study were effects of sensor travel speed and light source and intensity on image quality. When travel speed of image sensor increased from 0 to 10 mm/s, travel distance and number of pixel were increased to 3.30 mm and 9.4, respectively. This travel distances were not negligible even at a speed of 2 mm/s (i.e., 0.66 mm and 1.4), and image degradation was significant. Tests for effects of illumination intensity showed that 7 to 11 Lux seemed a good condition minimizing shade and reflection. When soil water content increased, illumination intensity should be greater to compensate decrease in brightness. Results of the paper would be useful for construction, test, and application of the sensor.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.1
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• pp.17-24
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• 2018

Military camera equipment has a problem that observability is inferior due to various shaking factors. In this paper, we propose an image stabilization algorithm considering performance and execution time to solve this problem and implemented it in Zynq SoC. We stabilized both the simple shaking in the fixed observation position and the sudden shaking in the moving observation position. The feature of the input image is extracted by the Sobel edge algorithm, the subblock with the large edge data is selected, and the motion vector, which is the compensation reference, is calculated through template matching using the 3-step search algorithm of the region of interest. In addition, the proposed algorithm can distinguish the shaking caused by the simple shaking and the movement by using the Kalman filter, and the stabilized image can be obtained by minimizing the loss of image information. To demonstrate the effectiveness of the proposed algorithm, experiments on various images were performed. In comparison, PSNR is improved in the range of 2.6725~3.1629 (dB) and image loss is reduced from 41% to 15%. On the other hand, we implemented the hardware-software integrated design using HLS of Xilinx SDSoC tool and confirmed that it operates at 32 fps on the Zynq board, and realized SoC that operates with real-time processing.

• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.850-853
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• 2017

In this paper, we propose an image analysis system based on omnidirectional image and object tracking image display using super wide angle camera. In order to generate spherical images, the projection process of converting from two wide-angle images to the equirectangular panoramic image was performed and the spherical image was expressed by converting rectangular to spherical coordinate system. Object tracking was performed by selecting the desired object initially, and KCF(Kernelized Correlation Filter) algorithm was used so that robust object tracking can be performed even when the object's shape is changed. In the initial dialog, the file and mode are selected, and then the result is displayed in the new dialog. If the object tracking mode is selected, the ROI is set by dragging the desired area in the new window.

• The KIPS Transactions:PartB
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• v.15B no.2
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• pp.103-112
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• 2008

Image-based motion capture technology is often used in making realistic computer animation. In this paper we try to implement image-based motion rendering by fixing a camera to a PC. Existing image-based rendering algorithms have disadvantages of high computational burden or low accuracy. The former disadvantage causes too long making-time of an animation. The latter disadvantage degrades reality in making realistic animation. To compensate for those disadvantages of the existing approaches, this paper presents an image-based motion rendering algorithm with low computational load and high estimation accuracy. In the proposed approach, an incremental motion rendering algorithm with low computational load is analyzed in the respect of optimal control theory and revised so that its estimation accuracy is enhanced. If we apply this proposed approach to optic motion capture systems, we can obtain additional advantages that motion capture can be performed without any markers, and with low cost in the respect of equipments and spaces.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.6
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• pp.557-567
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• 2015

With the increasing demands of 3D spatial information in urban environment, the importance of point clouds generation techniques have been increased. In particular, for as-built BIM, the point clouds with the high accuracy and density is required to describe the detail information of building components. Since the terrestrial LiDAR has high performance in terms of accuracy and point density, it has been widely used for as-built 3D modelling. However, the high cost of devices is obstacle for general uses, and the image-based 3D reconstruction technique is being a new attraction as an alternative solution. This paper compares the image-based 3D reconstruction technique and the terrestrial LiDAR in point of establishing the as-built BIM of outdoor structures. The point clouds generated from the image-based 3D reconstruction technique could roughly present the 3D shape of a building, but could not precisely express detail information, such as windows, doors and a roof of building. There were 13.2~28.9 cm of RMSE between the terrestrial LiDAR scanning data and the point clouds, which generated from smartphone and DSLR camera images. In conclusion, the results demonstrate that the image-based 3D reconstruction can be used in drawing building footprint and wireframe, and the terrestrial LiDAR is suitable for detail 3D outdoor modeling.

• The Journal of the Korea Contents Association
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• v.10 no.8
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• pp.186-197
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• 2010

Recent changes show that the goals of reproduction devices have changed from accurately reproducing scenes to improving user preference. It implies that the directions in developing cameras, the most common reproduction devices, are moving from performance-centered to quality-centered, from developers to users. Accepting such changes demand new standards in evaluating reproduction devices. This paper suggests a new method to evaluate the quality of images, based on cognitive properties of users. The quality of an image is a result oriented from the interaction of various attributes, therefore some functional tests are not enough to evaluate total quality of an image. In this respect, an evaluation model which integrates various physical attributes of an image is needed, that enables a third observer to subjectively evaluate the total quality of an image. In this paper, the experiment was carried out to 127 subjects, with the 84 test stimuli and 11 evaluation factors, followed by an factor analysis. The evaluation factors to assess the quality of images in this paper includes the results by cognitions of users and the properties of reproduction, the factors not only evaluate the quality but suggest how to improve them.