• Title/Summary/Keyword: Delta Image Information

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Color Correction Using Polynomial Regression in Film Scanner (다항회귀를 이용한 필름 스캐너에서의 색보정)

  • 김태현;백중환
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.40 no.1
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    • pp.43-50
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    • 2003
  • Today, the demand of image acquisition systems grows as the multimedia applications go on increasing greatly. Among the systems, film scanner is one of the systems, which can acquire high quality and high resolution images. However due to the nonlinear characteristic of the light source and sensor, colors of the original film image do not correspond to the colors of the scanned image. Therefore color correction mr the scanned digital image is essential in the film scanner. In this paper, polynomial regression method is applied for the color correction to CIE $L^{*}$ $a^{*}$ $b^{*}$ color model data converted from RGB color model data. A1so a film scanner hardware with 12 bit color resolution for each R, G, B and 2400 dpi was implemented by using TMS320C32 DSP chip and high resolution line sensor. An experimental result shows that the average color difference ($\Delta$ $E^{*}$$_{ab}$ ) is reduced from13.48 to 8.46.6.6.6.6.

A Study on Correlation between RUSLE and Estuary in Nakdong River Watershed (낙동강 유역의 토양유실량과 하구지형의 상관성 분석)

  • Hwang, Chang-Su;Kim, Kyung-Tag;Oh, Che-Young;Jin, Cheong-Gil;Choi, Chul-Uong
    • Journal of Korean Society for Geospatial Information Science
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    • v.18 no.3
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    • pp.3-10
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    • 2010
  • The development of various spatial information and GIS has led to the research on interpretation of natural phenomena and correlational studies. This study is aimed to analyze the correlation between RUSLE(Revised Universal Soil Loss Equation) around Nakdong River area during the period of 1955 to 2005 and the amount of area change in the islets at the estuary terrain calculated in the study "Change Detection at the Nakdong Estuary Delta using Satellite Image and GIS". For the calculation of RUSLE, The 'Revised-USLE' model, a modified USLE model commonly used in Korea was used. For the rainfall erosion factor to calculate and compare the area of islets, the actual observation data for one year before the observation of satellite image from all observatories across Korea was used. The correlation coefficient between RUSLE and area change of islets was 0.57 for Jinwoo Islet; 0.7 for Sinja Islet; 0.87 for Doyodeung. This results showed that there was a great influence from Doyodeung where the main water way of Nakdong River runs. This study showed that the study using USLE for various fields and through identifying the characteristics of each factor is useful to understand natural phenomenon in practice.

A New Fuzzy Supervised Learning Algorithm

  • Kim, Kwang-Baek;Yuk, Chang-Keun;Cha, Eui-Young
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.399-403
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    • 1998
  • In this paper, we proposed a new fuzzy supervised learning algorithm. We construct, and train, a new type fuzzy neural net to model the linear activation function. Properties of our fuzzy neural net include : (1) a proposed linear activation function ; and (2) a modified delta rule for learning algorithm. We applied this proposed learning algorithm to exclusive OR,3 bit parity using benchmark in neural network and pattern recognition problems, a kind of image recognition.

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Union and Division using Technique in Fingerprint Recognition Identification System

  • Park, Byung-Jun;Park, Jong-Min;Lee, Jung-Oh
    • Journal of information and communication convergence engineering
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    • v.5 no.2
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    • pp.140-143
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    • 2007
  • Fingerprint Recognition System is made up of Off-line treatment and On-line treatment; the one is registering all the information of there trieving features which are retrieved in the digitalized fingerprint getting out of the analog fingerprint through the fingerprint acquisition device and the other is the treatment making the decision whether the users are approved to be accessed to the system or not with matching them with the fingerprint features which are retrieved and database from the input fingerprint when the users are approaching the system to use. In matching between On-line and Off-line treatment, the most important thing is which features we are going to use as the standard. Therefore, we have been using "Delta" and "Core" as this standard until now, but there might have been some deficits not to exist in every person when we set them up as the standards. In order to handle the users who do not have those features, we are still using the matching method which enables us to make up of the spanning tree or the triangulation with the relations of the spanned feature. However, there are some overheads of the time on these methods and it is not sure whether they make the correct matching or not. In this paper, introduces a new data structure, called Union and Division, representing binary fingerprint image. Minutiae detecting procedure using Union and Division takes, on the average, 32% of the consuming time taken by a minutiae detecting procedure without using Union and Division.

A Study on the HEVC Video Encoder PMR Block Design (HEVC 비디오 인코더 PMR 블록 설계에 대한 연구)

  • Lee, Sukho;Lee, Jehyun
    • Journal of the Institute of Electronics and Information Engineers
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    • v.53 no.12
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    • pp.141-146
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    • 2016
  • HEVC/H.265 is the latest joint video coding standard proposed by ITU-T SG 16 WP and ISO/IEC JTC 1/SC29/WG 11. In H.265, pictures are divided into a sequence of coding tree units(CTUs), and the CTU further is partitioned into multiple CUs to adapt to various local characteristics. Its coding efficiency is approximately two times high compared to previous standard H.264/AVC. However according to the size of extended CU(coding unit) and transform block, the hardware size of PMR(prediction/mode decision/reconstruction) block within video encoder is about 4 times larger than previous standard. In this study, we propose a new less complex hardware architecture of PMR block which has the most high complexity within encoder without any noticeable PSNR loss. Using this simplified block, we can shrink the overall size the H.265 encoder. For FHD image, it operates at clocking frequency of 300 MHz and frame rate of 60 fps. And also for the test image, the Bjøntegaard Delta (BD) bit rate increase about average 30 % in PMR prediction block, and the total estimated gate count of PMR block is around 1.8 M.

Athermalized Design of Compact Optical System for Phone Camera (폰 카메라용 초소형 광학계의 온도보정 설계)

  • Park, Sung-Chan;You, Byoung-Taek;Lee, Jong-Ung
    • Korean Journal of Optics and Photonics
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    • v.20 no.3
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    • pp.148-155
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    • 2009
  • In this paper, we analysed what effect the design variables, such as refractive index, central thickness and radius of curvature, had on the first order properties and image quality of optical systems when temperature changed. The optical parameters were varied at each temperature, then the coupling and ruler methods were used to design an athermalized lens for a phone camera. This concept was first used to design the lens for a 1/3.2" 5M phone camera. The designed lens satisfies all the specifications for a phone camera, and the variations of the back focal length(${\Delta}BFL$) are reduced to $10{\mu}m$ for a temperature range of $-10^{\circ}C$ to $+60^{\circ}C$. Also, the TTL of 5.5 mm results in a compact system. All design concepts and results discussed in this paper are expected to be useful in development for the phone and CCTV camera.

Fingerprint Classification Based On the Entropy of Ridges (융선 엔트로피 계측을 이용한 지문 분류)

  • Park, Chang-Hee;Yoon, Kyung-Bae;Ko, Chang-Bae
    • The KIPS Transactions:PartB
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    • v.10B no.5
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    • pp.497-502
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    • 2003
  • Fingerprint classification plays a role of reduction of precise joining time and improvement of the accuracy in a large volume of database. Patterns of fingerprint are classified as 5 patterns : left loop, right loop, arch, whorl, and tented arch by numbers and the location of core point and delta point. The existing fingerprint classification is useful in a captured fingerprint image of core point and delta point using paper and ink. However, this system is unapplicable in modern Automatic Fingerprint Identification System (AFIS) because of problems such as size of input and way of input. To solve the problem, this study is to suggest the way of being able to improve accuracy of fingerprint by fingerprint classification based on the entropy of ridges using fingerprint captured mage of core point and prove this through the experiment.

Robust Orientation Estimation Algorithm of Fingerprint Images (노이즈에 강인한 지문 융선의 방향 추출 알고리즘)

  • Lee, Sang-Hoon;Lee, Chul-Han;Choi, Kyoung-Taek;Kim, Jai-Hie
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.45 no.1
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    • pp.55-63
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    • 2008
  • Ridge orientations of fingerprint image are crucial informations in many parts of fingerprint recognition such as enhancement, matching and classification. Therefore it is essential to extract the ridge orientations of image accurately because it directly affects the performance of the system. The two main properties of ridge orientation are 1) global characteristic(gradual change in whole part of fingerprint) and 2) local characteristic(abrupt change around core and delta points). When we only consider the local characteristic, estimated ridge orientations are well around singular points but not robust to noise. When the global characteristic is only considered, to estimate ridge orientation is robust to noise but cannot represent the orientation around singular points. In this paper, we propose a novel method for estimating ridge orientation which represents local characteristic specifically as well as be robust to noise. We reduce the noise caused by scar using iterative outlier rejection. We apply adaptive measurement resolution in each fingerprint area to estimate the ridge orientation around singular points accurately. We evaluate the performance of proposed method using synthetic fingerprint and FVC 2002 DB. We compare the accuracy of ridge orientation. The performance of fingerprint authentication system is evaluated using FVC 2002 DB.

A Study on A Deep Learning Algorithm to Predict Printed Spot Colors (딥러닝 알고리즘을 이용한 인쇄된 별색 잉크의 색상 예측 연구)

  • Jun, Su Hyeon;Park, Jae Sang;Tae, Hyun Chul
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.45 no.2
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    • pp.48-55
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    • 2022
  • The color image of the brand comes first and is an important visual element that leads consumers to the consumption of the product. To express more effectively what the brand wants to convey through design, the printing market is striving to print accurate colors that match the intention. In 'offset printing' mainly used in printing, colors are often printed in CMYK (Cyan, Magenta, Yellow, Key) colors. However, it is possible to print more accurate colors by making ink of the desired color instead of dotting CMYK colors. The resulting ink is called 'spot color' ink. Spot color ink is manufactured by repeating the process of mixing the existing inks. In this repetition of trial and error, the manufacturing cost of ink increases, resulting in economic loss, and environmental pollution is caused by wasted inks. In this study, a deep learning algorithm to predict printed spot colors was designed to solve this problem. The algorithm uses a single DNN (Deep Neural Network) model to predict printed spot colors based on the information of the paper and the proportions of inks to mix. More than 8,000 spot color ink data were used for learning, and all color was quantified by dividing the visible light wavelength range into 31 sections and the reflectance for each section. The proposed algorithm predicted more than 80% of spot color inks as very similar colors. The average value of the calculated difference between the actual color and the predicted color through 'Delta E' provided by CIE is 5.29. It is known that when Delta E is less than 10, it is difficult to distinguish the difference in printed color with the naked eye. The algorithm of this study has a more accurate prediction ability than previous studies, and it can be added flexibly even when new inks are added. This can be usefully used in real industrial sites, and it will reduce the attempts of the operator by checking the color of ink in a virtual environment. This will reduce the manufacturing cost of spot color inks and lead to improved working conditions for workers. In addition, it is expected to contribute to solving the environmental pollution problem by reducing unnecessarily wasted ink.

Edge Detection of Wide Band Width Spatial Frequency Components by the Diffusion Neural Network (확산 신경 회로망을 이용한 광대역 공간 주파수 성분의 윤곽선 검출)

  • Lee, Choong-Ho;Kwon, Yool;Kim, Jae-Chang;Nam, Ki-Gon;Yoon, Tae-Hoon
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.1
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    • pp.127-135
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    • 1995
  • The diffusion neural network forms a Gaussian distribution by transferring an excitation to the surround. A DOG(difference of two Gaussians) is obtained by the diffusion neural network. This type of the DOG, which can detect the intensity changes of an image, has the same shape as a LOG(Laplacian of a Gaussian:${\Delta}^2$G) and narrow band pass characteristics. In this paper we show that another type of the DOG which has a very narrow Gaussian for the excitatory and a very wide Gaussian for the inhibitory, can be formed by the diffusion process of this network, This type of the DOG has a wide band width in spatial frequency domain and can be used efficiently in detecting special type of edges.

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