• Journal of the Korea Organic Resources Recycling Association
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• v.18 no.1
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• pp.47-56
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• 2010

At present, 265 national food waste recycling facilities have been operated by public facilities 95 and private facilities 160. it has continuously installed a food waste treatment facility from 1997. The government set up and implemented guidelines and inspection standards for the installation and operation of the facilities. However, unclear detailed examination items, designs and process standards for the installation procedures of the facilities are causing problems due to the unskilled operation management system, decrease in efficiency and defects of a facility. This study conducted mail and site surveys on 95 public food waste recycling facilities that it suggest the ways to operate facilities which minimize problems. At the result of investigation, a pre-treatment facility was not installed 2 systems(2 inputting facilities) and hopper covers and food was overloaded. also the transportation amount was excessive. In case of a main treatment facility, the secondary environmental pollution was caused by inexperienced operation and the efficiency of the facility was reduced due to excessive input of food. also the operation management standards of the facilities were inappropriate. The odor and food waste leachate treatment facility is investigated as problems that are unskilled operation, lack of regular inspection and inappropriate capacity of the treatment facility. Based on the problems found through the investigation, it suggested some ways of efficient operation. this study might contribute to minimize mistakes and defects and improve the efficiency of install and operation course of food waste recycling facilities through finding.

• Korean Journal of Remote Sensing
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• v.33 no.6_3
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• pp.1223-1232
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• 2017

This paper presents an approach to detect changes caused by urban development over a large area using KOMPSAT optical images. In order to minimize the radiometric dissimilarities between the images acquired at different times, we apply the grid-based rough radiometric correction as a preprocessing to detect changes in a large area. To improve the accuracy of the change detection results for urban development, we mask-out non-interest areas such as water and forest regions by the use of land-cover map provided by the Ministry of Environment. The Change Vector Analysis(CVA) technique is applied to detect changes caused by urban development. To confirm the effectiveness of the proposed approach, a total of three study sites from Sejong City is constructed by combining KOMPSAT-2 images acquired on May 2007 and May 2016 and a KOMPSAT-3 image acquired on March 2014. As a result of the change detection accuracy evaluation for the study site generated from the KOMPSAT-2 image acquired on May 2007 and the KOMPSAT-3 image acquired on March 2014, the overall accuracy of change detection was about 91.00%. It is demonstrated that the proposed method is able to effectively detect urban development changes in a large area.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6D
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• pp.771-779
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• 2009

Digital topographical maps used for GIS DB are mainly produced by the traditional way of analogue aerial photogrammetry. Therefore, analogue photos are only available for digital mapping after preprocessing such as film developing, printing and scanning. However, digital aerial camera is able to get digital image directly without preprocessing and thus the performance and efficiency of photogrammetry are extremely increased. This study aims to investigate geometric stability of digital aerial frame camera DMC (Digital Modular Camera). In order to verify the geometric stability of digital aerial camera DMC, some different block conditions with and without cross strips, GPS/INS data and variation of GCPs are introduced in the block adjustment. The accuracy results of every block condition were compared each other by computation of residuals of exterior orientation (EO) parameters. Results of study shows that the geometric stability of the block adjustment with cross strips is increased about 30% against without cross strips. The accuracy of EO parameters of block adjustment with cross strips is also increased about 2cm for X-coordinate, 3cm for Y-coordinate, 3cm for Z-coordinate, and 6" for omega, 4" for phi and 3" for kappa.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.1
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• pp.1-12
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• 2008

In this paper, we present a real-time algorithm for recognizing the vehicle color from the indoor and outdoor vehicle images based on GPU (Graphics Processing Unit) acceleration. In the preprocessing step, we construct feature victors from the sample vehicle images with different colors. Then, we combine the feature vectors for each color and store them as a reference texture that would be used in the GPU. Given an input vehicle image, the CPU constructs its feature Hector, and then the GPU compares it with the sample feature vectors in the reference texture. The similarities between the input feature vector and the sample feature vectors for each color are measured, and then the result is transferred to the CPU to recognize the vehicle color. The output colors are categorized into seven colors that include three achromatic colors: black, silver, and white and four chromatic colors: red, yellow, blue, and green. We construct feature vectors by using the histograms which consist of hue-saturation pairs and hue-intensity pairs. The weight factor is given to the saturation values. Our algorithm shows 94.67% of successful color recognition rate, by using a large number of sample images captured in various environments, by generating feature vectors that distinguish different colors, and by utilizing an appropriate likelihood function. We also accelerate the speed of color recognition by utilizing the parallel computation functionality in the GPU. In the experiments, we constructed a reference texture from 7,168 sample images, where 1,024 images were used for each color. The average time for generating a feature vector is 0.509ms for the $150{\times}113$ resolution image. After the feature vector is constructed, the execution time for GPU-based color recognition is 2.316ms in average, and this is 5.47 times faster than the case when the algorithm is executed in the CPU. Our experiments were limited to the vehicle images only, but our algorithm can be extended to the input images of the general objects.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.61-73
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• 2014

This study reviewed an application of water quality estimation using an Airborne Hyperspectral Imagery (A-HSI) and tested a part of Han River water quality (especially suspended solid) estimation with available in-situ data. The estimation of water quality was processed two methods. One is using observation data as downwelling radiance to water surface and as scattering and reflectance into water body. Other is linear regression analysis with water quality in-situ measurement and upwelling data as at-sensor radiance (or reflectance). Both methods drive meaningful results of RS estimation. However it has more effects on the auxiliary dataset as water quality in-situ measurement and water body scattering measurement. The test processed a part of Han River located Paldang-dam downstream. We applied linear regression analysis with AISA eagle hyperspectral sensor data and water quality measurement in-situ data. The result of linear regression for a meaningful band combination shows $-24.847+0.013L_{560}$ as 560 nm in radiance (L) with 0.985 R-square. To comparison with Multispectral Imagery (MSI) case, we make simulated Landsat TM by spectral resampling. The regression using MSI shows -55.932 + 33.881 (TM1/TM3) as radiance with 0.968 R-square. Suspended Solid (SS) concentration was about 3.75 mg/l at in-situ data and estimated SS concentration by A-HIS was about 3.65 mg/l, and about 5.85mg/l with MSI with same location. It shows overestimation trends case of estimating using MSI. In order to upgrade value for practical use and to estimate more precisely, it needs that minimizing sun glint effect into whole image, constructing elaborate flight plan considering solar altitude angle, and making good pre-processing and calibration system. We found some limitations and restrictions such as precise atmospheric correction, sample count of water quality measurement, retrieve spectral bands into A-HSI, adequate linear regression model selection, and quantitative calibration/validation method through the literature review and test adopted general methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.8C
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• pp.651-660
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• 2010

In this paper, we implement an efficient histogram-based prefiltering to compensate the illumination mismatches in regions between neighboring views. In multi-view video, such illumination disharmony can primarily occur on account of different camera location and orientation and an imperfect camera calibration. This discrepancy can cause the performance decrease of multi-view video coding(MVC) algorithm. A histogram matching algorithm can be exploited to make up for these differences in a prefiltering step. Once all camera frames of a multi-view sequence are adjusted to a predefined reference through the histogram matching, the coding efficiency of MVC is improved. However general frames of multi-view video sequence are composed of several regions with different color composition and their histogram distribution which are mutually independent of each other. In addition, the location and depth of these objects from sequeuces captured from different cameras can be different with different frames. Thus we propose a new algorithm which classify a image into several subpartitions by its depth information first and then histogram matching is performed for each region individually. Experimental results show that the compression ratio for the proposed algorithm is improved comparing with the conventional image-based algorithms.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2004.11a
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• pp.64-66
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• 2004

When examing patients with DRs it is necessary to remove bad pixels and lines and to correct non-uniform offsets and x-ray field. For non-uniformity correction a flat field x-ray image is needed, and to obtain it the center of detector is usually aligned with the focal spot of the x-ray tube, which is conserved when examing patients to preserve the flat field. In some of radiographic techniques, however, it is necessary to move the x-ray tube off the center position of detector or tilt the detector. We investigated the effect of detector tilting on the non-uniformity correction, and propose a method to reduce the effect using a new algorithm. The flat field of X-ray in the DR detector could be guaranteed with this result.

• Journal of KIISE:Software and Applications
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• v.29 no.11
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• pp.809-817
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• 2002

This paper describes a new face detection method that is a pre-processing algorithm for on-line face recognition. To complement the weakness of using only edge or rotor features from previous face detection method, we propose the two types of face detection method. The one is a combined method with edge and color features and the other is a center area color sampling method. To prevent connecting the people's face area and the background area, which have same colors, we propose a new adaptive edge detection algorithm firstly. The adaptive edge detection algorithm is robust to illumination variance so that it extracts lots of edges and breakouts edges steadily in border between background and face areas. Because of strong edge detection, face area appears one or multi regions. We can merge these isolated regions using color information and get the final face area as a MBR (Minimum Bounding Rectangle) form. If the size of final face area is under or upper threshold, color sampling method in center area from input image is used to detect new face area. To evaluate the proposed method, we have experimented with 2,100 face images. A high face detection rate of 96.3% has been obtained.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.6
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• pp.315-320
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• 2017

Estimating the correct pose of augmented objects on the real camera view efficiently is one of the most important questions in image tracking area. In computer vision, Homography is used for camera pose estimation in augmented reality system with markerless. To estimating Homography, several algorithm like SURF features which extracted from images are used. Based on extracted features, Homography is estimated. For this purpose, RANSAC algorithm is well used to estimate homography and DCS-RANSAC algorithm is researched which apply constraints dynamically based on Constraint Satisfaction Problem to improve performance. In DCS-RANSAC, however, the dataset is based on pattern of feature distribution of images manually, so this algorithm cannot classify the input image, pattern of feature distribution is not recognized in DCS-RANSAC algorithm, which lead to reduce it's performance. To improve this problem, we suggest the KCS-RANSAC algorithm using K-means clustering in CS-RANSAC to cluster the images automatically based on pattern of feature distribution and apply constraints to each image groups. The suggested algorithm cluster the images automatically and apply the constraints to each clustered image groups. The experiment result shows that our KCS-RANSAC algorithm outperformed the DCS-RANSAC algorithm in terms of speed, accuracy, and inlier rate.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.1
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• pp.20-27
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• 2010

This paper describes a design of 5-stage pipelined de-blocking filter with power reduction scheme and proposes a efficient memory architecture and filter order for high performance H.264/AVC Decoder. Generally the de-blocking filter removes block boundary artifacts and enhances image quality. Nevertheless filter has a few disadvantage that it requires a number of memory access and iterated operations because of filter operation for 4 time to one edge. So this paper proposes a optimized filter ordering and efficient hardware architecture for the reduction of memory access and total filter cycles. In proposed filter parallel processing is available because of structured 5-stage pipeline consisted of memory read, threshold decider, pre-calculation, filter operation and write back. Also it can reduce power consumption because it uses a clock gating scheme which disable unnecessary clock switching. Besides total number of filtering cycle is decreased by new filter order. The proposed filter is designed with Verilog-HDL and functionally verified with the whole H.264/AVC decoder using the Modelsim 6.2g simulator. Input vectors are QCIF images generated by JM9.4 standard encoder software. As a result of experiment, it shows that the filter can make about 20% total filter cycles reduction and it requires small transposition buffer size.