• Title/Summary/Keyword: image fingerprinting

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Perceptual Bound-Based Asymmetric Image Hash Matching Method

  • Seo, Jiin Soo
    • Journal of Korea Multimedia Society
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    • v.20 no.10
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    • pp.1619-1627
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    • 2017
  • Image hashing has been successfully applied for the problems associated with the protection of intellectual property, management of large database and indexation of content. For a reliable hashing system, improving hash matching accuracy is crucial. In order to improve the hash matching performance, we propose an asymmetric hash matching method using the psychovisual threshold, which is the maximum amount of distortion that still allows the human visual system to identity an image. A performance evaluation over sets of image distortions shows that the proposed asymmetric matching method effectively improves the hash matching performance as compared with the conventional Hamming distance.

Accelerating Magnetic Resonance Fingerprinting Using Hybrid Deep Learning and Iterative Reconstruction

  • Cao, Peng;Cui, Di;Ming, Yanzhen;Vardhanabhuti, Varut;Lee, Elaine;Hui, Edward
    • Investigative Magnetic Resonance Imaging
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    • v.25 no.4
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    • pp.293-299
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    • 2021
  • Purpose: To accelerate magnetic resonance fingerprinting (MRF) by developing a flexible deep learning reconstruction method. Materials and Methods: Synthetic data were used to train a deep learning model. The trained model was then applied to MRF for different organs and diseases. Iterative reconstruction was performed outside the deep learning model, allowing a changeable encoding matrix, i.e., with flexibility of choice for image resolution, radiofrequency coil, k-space trajectory, and undersampling mask. In vivo experiments were performed on normal brain and prostate cancer volunteers to demonstrate the model performance and generalizability. Results: In 400-dynamics brain MRF, direct nonuniform Fourier transform caused a slight increase of random fluctuations on the T2 map. These fluctuations were reduced with the proposed method. In prostate MRF, the proposed method suppressed fluctuations on both T1 and T2 maps. Conclusion: The deep learning and iterative MRF reconstruction method described in this study was flexible with different acquisition settings such as radiofrequency coils. It is generalizable for different in vivo applications.

Unauthorized person tracking system in video using CNN-LSTM based location positioning

  • Park, Chan;Kim, Hyungju;Moon, Nammee
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.12
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    • pp.77-84
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    • 2021
  • In this paper, we propose a system that uses image data and beacon data to classify authorized and unauthorized perosn who are allowed to enter a group facility. The image data collected through the IP camera uses YOLOv4 to extract a person object, and collects beacon signal data (UUID, RSSI) through an application to compose a fingerprinting-based radio map. Beacon extracts user location data after CNN-LSTM-based learning in order to improve location accuracy by supplementing signal instability. As a result of this paper, it showed an accuracy of 93.47%. In the future, it can be expected to fusion with the access authentication process such as QR code that has been used due to the COVID-19, track people who haven't through the authentication process.

A study on Prevent fingerprints Collection in High resolution Image (고해상도로 찍은 이미지에서의 손가락 지문 채취 방지에 관한 연구)

  • Yoon, Won-Seok;Kim, Sang-Geun
    • Journal of Convergence for Information Technology
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    • v.10 no.6
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    • pp.19-27
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    • 2020
  • In this study, Developing high resolution camera and Social Network Service sharing image can be easily getting images, it cause about taking fingerprints to easy from images. So I present solution about prevent to taking fingerprints. this technology is develop python using to opencv, blur libraries. First of all 'Hand Key point Detection' algorithm is used to locate the hand in the image. Using this algorithm can be find finger joints that can be protected while minimizing damage in the original image by using the coordinates of separate blurring the area of fingerprints in the image. from now on the development of accurate finger tracking algorithms, fingerprints will be protected by using technology as an internal option for smartphone camera apps from high resolution images.

An Identification and Feature Search System for Scanned Comics (스캔 만화도서 식별 및 특징 검색 시스템)

  • Lee, Sang-Hoon;Choi, Nakyeon;Lee, Sanghoon
    • Journal of KIISE:Databases
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    • v.41 no.4
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    • pp.199-208
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    • 2014
  • In this paper, we represent a system of identification and feature search for scanned comics in consideration of their content characteristics. For creating the feature of the scanned comics, we utilize a method of hierarchical symmetry fingerprinting. Proposed identification and search system is designed to give online service provider, such as Webhard, an immediate identification result under conditions of huge volume of the scanned comics. In simulation part, we analyze the robustness of the identification of the fingerprint to image modification such as rotation and translation. Also, we represent a structure of database for fast matching in feature point database, and compare search performance between other existing searching methods such as full-search and most significant feature search.

A preliminary study and its application for the development of the quantitative evaluation method of developed fingerprints on porous surfaces using densitometric image analysis (다공성 표면에서 현출된 지문의 정량적인 평가방법 개발을 위한 농도계 이미지 분석을 이용한 선행연구 및 응용)

  • Cho, Jae-Hyun;Kim, Hyo-Won;Kim, Min-Sun;Choi, Sung-Woon
    • Analytical Science and Technology
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    • v.29 no.3
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    • pp.142-153
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    • 2016
  • In crime scene investigation, fingerprint identification is regarded to be one of the most important techniques for personal identification. However, objective and unbiased evaluation methods that would compare the fingerprints with diverse available and developing methods are currently lacking. To develop an objective and quantitative method to improve fingerprint evaluation, a preliminary study was performed to extract useful research information from the analysis with densitometric image analysis (CP Atlas 2.0) and the Automated Fingerprint Identification System (AFIS) for the developed fingerprints on porous surfaces. First, inked fingerprints obtained by varying pressure (kg.f) and pressing time (sec.) to find optimal conditions for obtaining fingerprint samples were analyzed, because they could provide fingerprints of a relatively uniform quality. The extracted number of minutiae from the analysis with AFIS was compared with the calculated areas of friction ridge peaks from the image analysis. Inked fingerprints with a pressing pressure of 1.0 kg.f for 5 seconds provided the most visually clear fingerprints, the highest number of minutiae points, and the largest average area of the peaks of the friction ridge. In addition, the images of the developed latent fingerprints on thermal paper with the iodine fuming method were analyzed. Fingerprinting condition of 1.0 kg.f/5 sec was also found to be optimal when generating highest minutiae number and the largest average area of peaks of ridges. Additionally, when the concentration of ninhydrin solution (0.5 % vs. 5 %) was used to compare the developed latent fingerprints on print paper, the best fingerprinting condition was 2.0 kg.f/5 sec and 5 % of ninhydrin concentration. It was confirmed that the larger the average area of the peaks generated by the image analysis, the higher the number of minutiae points was found. With additional tests for fingerprint evaluation using the densitometric image analysis, this method can prove to be a new quantitative and objective assessment method for fingerprint development.

Proteomic Analysis of Protein Expression Patterns Associated with Astaxanthin Accumulation by Green Alga Haematococcus pluvialis (Chlorophyceae) Under High Light Stress

  • Kim Jeong-Dong;Lee Woo-Sung;Kim Beob-Min;Lee Choul-Gyun
    • Journal of Microbiology and Biotechnology
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    • v.16 no.8
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    • pp.1222-1228
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    • 2006
  • Two kinds of Haematococcus pluvialis cells (green vegetative cells cultivated under optimal cell culture conditions and red cyst cells maintained under high light stress conditions to induce astaxanthin production) were used to investigate the protein expression profiles by two-dimensional electrophoresis, image analysis, and peptide mass fingerprinting. The cellular accumulation of astaxanthin was evident after exposure to high light intensity and reached the maximum cellular level after 78 h of high light stress. In a 2-D electrophoresis analysis, 22 proteins were upregulated over 2-fold in the red cyst cells when compared with the green vegetative cells and selected for further analysis by chemically assisted fragmentation (CAF)-MALDI-TOF sequencing to identify the protein functions. Among 22 different spots, several key enzymes specific to the carotenoid pathway, including isopentenyl pyrophosphate isomerase (IPP) and lycopene $\beta$-cyclase, appeared in H. pluvialis after exposure to high light intensity. Therefore, IPP and lycopene $\beta$-cyclase would appear to be involved with carotenoid accumulation in the cytoplasm, as these peptides were preferentially upregulated by high light intensity preceding an increase in carotenoid, and only these forms were detected in the red cyst cells.

Proteomic Analysis of the Hydrophobic Fraction of Mesenchymal Stem Cells Derived from Human Umbilical Cord Blood

  • Jeong, Ju Ah;Lee, Yoon;Lee, Woobok;Jung, Sangwon;Lee, Dong-Seong;Jeong, Namcheol;Lee, Hyun Soo;Bae, Yongsoo;Jeon, Choon-Ju;Kim, Hoeon
    • Molecules and Cells
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    • v.22 no.1
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    • pp.36-43
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    • 2006
  • Mesenchymal stem cells (MSCs) are promising candidates for cell therapy and tissue engineering, but their application has been impeded by lack of knowledge of their core biological properties. In order to identify MSC-specific proteins, the hydrophobic protein fraction was individually prepared from two different umbilical cord blood (UCB)-derived MSC populations; these were then subjected to two-dimensional (2D) gel electrophoresis and peptide mass fingerprinting matrix-assisted laser desorption/ionization (MALDI)-time of flight (TOF)-mass spectrometry (MS). Although the 2D gel patterns differed somewhat between the two samples, computer-assisted image analysis identified shared protein spots. 35 spots were reliably identified corresponding to 32 different proteins, many of which were chaperones. Based on their primary sub-cellular locations the proteins could be grouped into 6 categories: extracellular, cell surface, endoplasmic reticular, mitochondrial, cytoplasmic and cytoskeletal proteins. This map of the water-insoluble proteome may provide valuable insights into the biology of the cell surface and other compartments of human MSCs.

A Novel Copyright Protection for Digital Images Using Magnitude and Orientation of Edge (영상의 에지 크기와 각도를 이용한 정지영상 보호 기법)

  • Shin, Jin-Wook;Min, Byung-Jun;Yoon, Sook
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.3C
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    • pp.262-270
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    • 2008
  • We propose a technique to protect digital images using the magnitude and orientation of their edges. The proposed technique uses the content-associated copyright message generated by combining the original copyright message with the magnitude and orientation of some edges of a digital image. It enables the distribution of the original copyright message without any distortion of original digital images by avoiding embedment of the original copyright message into images. In addition to the advantage in the image quality, it also has a relatively low computational complexity by using simple operations to generate the content-associated copyright message. To verify the proposed technique, we performed experiments on its robustness to the external attacks such as histogram equalization, median filtering, rotation, and cropping. Experimental results on restoring the copyright message from images distorted by attacks show that more than 90%, on the average, can be recovered.

CNN-based Adaptive K for Improving Positioning Accuracy in W-kNN-based LTE Fingerprint Positioning

  • Kwon, Jae Uk;Chae, Myeong Seok;Cho, Seong Yun
    • Journal of Positioning, Navigation, and Timing
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    • v.11 no.3
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    • pp.217-227
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    • 2022
  • In order to provide a location-based services regardless of indoor or outdoor space, it is important to provide position information of the terminal regardless of location. Among the wireless/mobile communication resources used for this purpose, Long Term Evolution (LTE) signal is a representative infrastructure that can overcome spatial limitations, but the positioning method based on the location of the base station has a disadvantage in that the accuracy is low. Therefore, a fingerprinting technique, which is a pattern recognition technology, has been widely used. The simplest yet widely applied algorithm among Fingerprint positioning technologies is k-Nearest Neighbors (kNN). However, in the kNN algorithm, it is difficult to find the optimal K value with the lowest positioning error for each location to be estimated, so it is generally fixed to an appropriate K value and used. Since the optimal K value cannot be applied to each estimated location, therefore, there is a problem in that the accuracy of the overall estimated location information is lowered. Considering this problem, this paper proposes a technique for adaptively varying the K value by using a Convolutional Neural Network (CNN) model among Artificial Neural Network (ANN) techniques. First, by using the signal information of the measured values obtained in the service area, an image is created according to the Physical Cell Identity (PCI) and Band combination, and an answer label for supervised learning is created. Then, the structure of the CNN is modeled to classify K values through the image information of the measurements. The performance of the proposed technique is verified based on actual data measured in the testbed. As a result, it can be seen that the proposed technique improves the positioning performance compared to using a fixed K value.