• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.225-230
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• 2020

Machine learning is an algorithm which learns a computer based on the data so that the computer can identify the trend of the data and predict the output of new input data. Machine learning can be classified into supervised learning, unsupervised learning, and reinforcement learning. Supervised learning is a way of learning a machine with given label of data. In other words, a method of inferring a function of the system through a pair of data and a label is used to predict a result using a function inferred about new input data. If the predicted value is continuous, regression analysis is used. If the predicted value is discrete, it is used as a classification. A result of analysis, no. 8 (5, 3.4, setosa), 27 (5, 3.4, setosa), 41 (5, 3.5, setosa), 44 (5, 3.5, setosa) and 40 (5.1, 3.4, setosa) in Table 3 were classified as the most similar Iris flower. Therefore, theoretical practical are suggested.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1424-1436
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• 2020

Although huge progress has been made in current image segmentation work, there are still no efficient segmentation strategies for tree image which is taken from natural environment and contains complex background. To improve those problems, we propose a method for tree image segmentation combining adaptive mean shifting with image abstraction. Our approach perform better than others because it focuses mainly on the background of image and characteristics of the tree itself. First, we abstract the original tree image using bilateral filtering and image pyramid from multiple perspectives, which can reduce the influence of the background and tree canopy gaps on clustering. Spatial location and gray scale features are obtained by step detection and the insertion rule method, respectively. Bandwidths calculated by spatial location and gray scale features are then used to determine the size of the Gaussian kernel function and in the mean shift clustering. Furthermore, the flood fill method is employed to fill the results of clustering and highlight the region of interest. To prove the effectiveness of tree image abstractions on image clustering, we compared different abstraction levels and achieved the optimal clustering results. For our algorithm, the average segmentation accuracy (SA), over-segmentation rate (OR), and under-segmentation rate (UR) of the crown are 91.21%, 3.54%, and 9.85%, respectively. The average values of the trunk are 92.78%, 8.16%, and 7.93%, respectively. Comparing the results of our method experimentally with other popular tree image segmentation methods, our segmentation method get rid of human interaction and shows higher SA. Meanwhile, this work shows a promising application prospect on visual reconstruction and factors measurement of tree.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.117-123
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• 2022

Currently the number of COVID-19 cases is increasing rapidly around the world. One way to restrict the spread of COVID-19 infection is to find confirmed cases using rapid diagnosis. The previously proposed group testing problem assumed without measurement noise, but recently, false positive and false negative cases have occurred during COVID-19 testing. In this paper, we define the noisy group testing problem and analyze how much measurement noise affects the performance. In this paper, we show that the group testing system should be designed to be less susceptible to measurement noise when conducting group testing with a low positive rate of COVID-19 infection. And compared with other developed reconstruction algorithms, our proposed algorithm shows superior performance in noisy group testing.

• Journal of Korea Entertainment Industry Association
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• v.5 no.1
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• pp.127-133
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• 2011

Characters in natural image are an important information with various context. Previous work of character region detection algorithms is not detect of character region in case of image complexity and the surrounding lighting, similar background to character, so this paper propose an method of character region detection in natural image using edge and connected component by morphological reconstructions. Firstly, we detect edge using Canny-edge detector and connected component with local min/max value by morphological reconstructed-operation in gray-scale image, and labeling each of detected connected component elements. lastly, detected candidate of text regions was merged for generation for one candidate text region, Final text region detected by checking the similarity and adjacency of neighbor of text candidate individual character. As the results of experiments, proposed algorithm improved the correctness of character regions detection using edge and connected components.

• Progress in Medical Physics
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• v.19 no.4
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• pp.209-218
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• 2008

According to improved radiation therapy technology such as IMRT and proton therapy, the accuracy of patient alignment system is more emphasized and IGRT is dominated research field in radiation oncology. We proposed to study the feasibility of cone-beam CT system using simple x-ray imaging systems for image guided proton therapy at National Cancer Center. 180 projection views ($2,304{\times}3,200$, 14 bit with 127 ${\mu}m$ pixel pitch) for the geometrical calibration phantom and humanoid phantoms (skull, abdomen) were acquired with $2^{\circ}$ step angle using x-ray imaging system of proton therapy gantry room ($360^{\circ}$ for 1 rotation). The geometrical calibration was performed for misalignments between the x-ray source and the flat-panel detector, such as distances and slanted angle using available algorithm. With the geometrically calibrated projection view, Feldkamp cone-beam algorithm using Ram-Lak filter was implemented for CBCT reconstruction images for skull and abdomen phantom. The distance from x-ray source to the gantry isocenter, the distance from the flat panel to the isocenter were calculated as 1,517.5 mm, 591.12 mm and the rotated angle of flat panel detector around x-ray beam axis was considered as $0.25^{\circ}$. It was observed that the blurring artifacts, originated from the rotation of the detector, in the reconstructed toomographs were significantly reduced after the geometrical calibration. The demonstrated CBCT images for the skull and abdomen phantoms are very promising. We performed the geometrical calibration of the large gantry rotation system with simple x-ray imaging devices for CBCT reconstruction. The CBCT system for proton therapy will be used as a main patient alignment system for image guided proton therapy.

• Progress in Medical Physics
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• v.7 no.1
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• pp.65-77
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• 1996

Using the 2-D and 3-D Hoffman brain phantom, 3-D Jaszczak phantom and Single Photon Emission Computed Tomography, the effects of data acquisition parameter, attenuation, noise, scatter and reconstruction algorithm on image quantitation as well as image quality were studied. For the data acquisition parameters, the images were acquired by changing the increment angle of rotation and the radius. The less increment angle of rotation resulted in superior image quality. Smaller radius from the center of rotation gave better image quality, since the resolution degraded as increasing the distance from detector to object increased. Using the flood data in Jaszczak phantom, the optimal attenuation coefficients were derived as 0.12cm$\^$-1/ for all collimators. Consequently, the all images were corrected for attenuation using the derived attenuation coefficients. It showed concave line profile without attenuation correction and flat line profile with attenuation correction in flood data obtained with jaszczak phantom. And the attenuation correction improved both image qulity and image quantitation. To study the effects of noise, the images were acquired for 1min, 2min, 5min, 10min, and 20min. The 20min image showed much better noise characteristics than 1min image indicating that increasing the counting time reduces the noise characteristics which follow the Poisson distribution. The images were also acquired using dual-energy windows, one for main photopeak and another one for scatter peak. The images were then compared with and without scatter correction. Scatter correction improved image quality so that the cold sphere and bar pattern in Jaszczak phantom were clearly visualized. Scatter correction was also applied to 3-D Hoffman brain phantom and resulted in better image quality. In conclusion, the SPECT images were significantly affected by the factors of data acquisition parameter, attenuation, noise, scatter, and reconstruction algorithm and these factors must be optimized or corrected to obtain the useful SPECT data in clinical applications.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.29-40
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• 2005

According as base of digital hologram has been magnified, discussion of compression technology is expected as a international standard which defines the compression technique of 3D image and video has been progressed in form of 3DAV which is a part of MPEG. As we can identify in case of 3DAV, the coding technique has high possibility to be formed into the hybrid type which is a merged, refined, or mixid with the various previous technique. Therefore, we wish to present the relationship between various image/video coding techniques and digital hologram In this paper, we propose an efficient coding method of digital hologram using standard compression tools for video and image. At first, we convert fringe patterns into video data using a principle of CGH(Computer Generated Hologram), and then encode it. In this research, we propose a compression algorithm is made up of various method such as pre-processing for transform, local segmentation with global information of object image, frequency transform for coding, scanning to make fringe to video stream, classification of coefficients, and hybrid video coding. Finally the proposed hybrid compression algorithm is all of these methods. The tool for still image coding is JPEG2000, and the toots for video coding include various international compression algorithm such as MPEG-2, MPEG-4, and H.264 and various lossless compression algorithm. The proposed algorithm illustrated that it have better properties for reconstruction than the previous researches on far greater compression rate above from four times to eight times as much. Therefore we expect that the proposed technique for digital hologram coding is to be a good preceding research.

• Progress in Medical Physics
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• v.27 no.1
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• pp.1-7
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• 2016

In this work, we considered a compressed-sensing (CS)-based image deblurring scheme with a total-variation (TV) regularization penalty for improving image characteristics in digital tomosynthesis (DTS). We implemented the proposed image deblurring algorithm and performed a systematic simulation to demonstrate its viability. We also performed an experiment by using a table-top setup which consists of an x-ray tube operated at $90kV_p$, 6 mAs and a CMOS-type flat-panel detector having a $198-{\mu}m$ pixel resolution. In the both simulation and experiment, 51 projection images were taken with a tomographic angle range of ${\theta}=60^{\circ}$ and an angle step of ${\Delta}{\theta}=1.2^{\circ}$ and then deblurred by using the proposed deblurring algorithm before performing the common filtered-backprojection (FBP)-based DTS reconstruction. According to our results, the image sharpness of the recovered x-ray images and the reconstructed DTS images were significantly improved and the cross-plane spatial resolution in DTS was also improved by a factor of about 1.4. Thus the proposed deblurring scheme appears to be effective for the blurring problems in both conventional radiography and DTS and is applicable to improve the present image characteristics.

• Korean Journal of Construction Engineering and Management
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• v.18 no.6
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• pp.47-56
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• 2017

As of 2017, there are 848 million households living in apartment and 55.87% of Aged apartments over 15 years old. The allowable standard for remodeling the apartment is more than 15 years and the market for remodeling the apartment will continue to increase. For the success of the remodeling project feasibility analysis is important but the existing feasibility analysis of new construction and reconstruction is being used for remodeling feasibility analysis. Therefore, it is necessary to study the feasibility analysis of customized remodeling without increasing the number of households according to the building law. Purpose of this paper is to develop a feasibility analysis methodology for customized remodeling projects by deriving the factors affecting the formation of land prices and building prices in apartment. According to the concept of price formation of the apartment, the analysis method of the customized remodeling of the old apartment using the factors affecting the Land Price Indexes, Officially Assessed Individual Land Price, House Price Indexes, and Officially Assessed Individual House Price was suggested. The Stair Price Algorithm developed in this research can be utilized at the stage of selecting remodeling contractors after the remodeling housing association is established.

• Korean Journal of Optics and Photonics
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• v.18 no.6
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• pp.375-382
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• 2007

The Shack-Hartmann wavefront sensor is composed of a lenslet array generating the spot images from which local slope is calculated and overall wavefront is measured. Generally the principle of wavefront reconstruction is that the spot centroid of each lenslet array is calculated from pixel intensity values in its subaperture, and then overall wavefront is reconstructed by the local slope of the wavefront obtained by deviations from reference positions. Hence the spot image of each lenslet array has to remain in its subaperture for exact measurement of the wavefront. However the spot of each lenslet array deviates from its subaperture area when a wavefront with large local slopes enters the Shack-Hartmann sensor. In this research, we propose a spot image searching method that finds the area of each measured spot image flexibly and determines the centroid of each spot in its area Also the algorithms that match these centroids to their reference points unequivocally, even if some of them are situated off the allocated subaperture, are proposed. Finally we verify the proposed algorithm with the test of a defocus measurement through experimental setup for the Shack-Hartmann wavefront sensor. It has been shown that the proposed algorithm can expand the dynamic range without additional devices.