• Title/Summary/Keyword: random points

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A Study on the Hair Line detection Using Feature Points Matching in Hair Beauty Fashion Design (헤어 뷰티 패션 디자인 선별을 위한 특징 점 정합을 이용한 헤어 라인 검출)

  • 송선희;나상동;배용근
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.7 no.5
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    • pp.934-940
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    • 2003
  • In this paper, hair beauty fashion design feature points detection system is proposed. A hair models and hair face is represented as a graph where the nodes are placed at facial feature points labeled by their Gabor features and the edges are describes their spatial relations. An innovative flexible feature matching is proposed to perform features correspondence between hair models and the input image. This matching hair model works like random diffusion process in the image space by employing the locally competitive and globally corporative mechanism. The system works nicely on the face images under complicated background. pose variations and distorted by accessories. We demonstrate the benefits of our approach by its implementation on the face identification system.

Hybrid Retrieval Machine for Recognizing 3-D Protein Molecules (3차원 단백질 분자 인식을 위한 복합 추출기)

  • Lee, Hang-Chan
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.59 no.5
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    • pp.990-995
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    • 2010
  • Harris corner detector is commonly used to detect feature points for recognizing 2-D or 3-D objects. However, the feature points calculated from both of query and target objects need to be same positions to guarantee accurate recognitions. In order to check the positions of calculated feature points, we generate a Huffman tree which is based on adjacent feature values as inputs. However, the structures of two Huffman trees will be same as long as both of a query and targets have same feature values no matter how different their positions are. In this paper, we sort feature values and calculate the Euclidean distances of coordinates between two adjacent feature values. The Huffman Tree is generated with these Euclidean distances. As a result, the information of point locations can be included in the generated Huffman tree. This is the main strategy for accurate recognitions. We call this system as the HRM(Hybrid Retrieval Machine). This system works very well even when artificial random noises are added to original data. HRM can be used to recognize biological data such as proteins, and it will curtail the costs which are required to biological experiments.

Edgeworth and Cornish-Fisher Expansion for the Non-normal t

  • Hwang, Hark
    • Journal of the Korean Statistical Society
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    • v.7 no.1
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    • pp.3-10
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    • 1978
  • Let $X_i,...,X_n$ be a random sample from a distribution with cumulants $K_1, K_2,...$. The statistic $t = \frac{\sqrt{x}(\bar{X}-K_1)}{S}$ has the well-known 'student' distribution with $\nu = n-1$ degrees of freedom if the $X_i$ are normally distributed (i.e., $K_i = 0$ for $i \geq 3$). An Edgeworth series expansion for the distribution of t when the $X_i$ are not normally distributed is obtained. The form of this expansion is Prob $(t

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A Flexible Feature Matching for Automatic face and Facial feature Points Detection (얼굴과 얼굴 특징점 자동 검출을 위한 탄력적 특징 정합)

  • 박호식;손형경;정연길;배철수
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2002.05a
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    • pp.608-612
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    • 2002
  • An automatic face and facial feature points(FFPs) detection system is proposed. A face is represented as a graph where the nodes are placed at facial feature points(FFPs) labeled by their Gabor features md the edges are describes their spatial relations. An innovative flexible feature matching is proposed to perform features correspondence between models and the input image. This matching model works likes random diffusion process in the image spare by employing the locally competitive and globally corporative mechanism. The system works nicely on the face images under complicated background, pose variations and distorted by facial accessories. We demonstrate the benefits of our approach by its implementation on the fare identification system.

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A Technique of Watermark Generation and Similarity Embedding for Still Images Based on Cross Reference Points (교차참조점에 기반한 정지영상의 워터마크 생성 및 유사성 삽입 기법)

  • Lee, Hang-Chan
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.8
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    • pp.1484-1490
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    • 2007
  • The Cross Reference Point(CRP) is a robust method for finding salient points in watermarking systems because it is based on the geometrical structure of a normalized image in order to avoid pointing error caused by digital attacks. After normalization of an image, the 100 CRPs are calculated. Next, the 100 blocks centered by CRPS are formed. These 100 blocks are arranged using a secrete key. Each boundary of 50 out of 100 blocks is surrounded by 8 blocks which are selected by the ordered number of a preceding block. This number is a seed of random number generator for selecting 8 out of 50 blocks. The search area of a center block is formed by a secrete key. The pixels of a center block are quantized to 10 levels by predefined thresholds. The watermarks are generated by the 50 quantized center blocks. These watermarks are embedded directly in the remaining 50 blocks. In other words, 50 out of 100 blocks are utilized to generate watermarks and the remaining 50 blocks are used to watermark embedding. Because the watermarks are generated in the given images, we can successfully detect watermarks after several digital attacks. The reason is that the blocks for the generation and detection of watermarks are equally affected by digital attacks except for the case of local distortion such as cropping.

Knowledge, Experience, and Attitudes of Nurses at Long-Term Care Hospitals regarding Advance Directives

  • Go Eun, Park;Nae Young, Lee
    • Journal of Hospice and Palliative Care
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    • v.25 no.4
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    • pp.139-149
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    • 2022
  • Purpose: The purpose of this study was to promote awareness of the need for advance directives (ADs) and to provide baseline data for the development of a nurse training program about ADs. Methods: Nurses at eight long-term care hospitals in Busan and South Gyeongsang Province (N=143) were recruited using the random sampling method from December 2018 to January 2019. Data were obtained using a structured self-reported questionnaire to assess their knowledge, experience, and attitudes regarding ADs. Data were analyzed in SPSS 22.0 using descriptive statistics, the t-test, analysis of variance, the Scheffé test, Pearson's correlation coefficient, and stepwise multiple regression analysis. Results: The mean scores were 7.79±1.39 points for knowledge, 1.92±2.00 points for experience, and 2.80±0.24 points for attitudes regarding ADs. Knowledge and experience (r=0.32, P<0.001) had a positive correlation with knowledge and attitudes (r=0.17, P=0.39). Conclusion: According to the results, nurses generally had a high level of knowledge regarding ADs, which resulted in a positive attitude toward ADs. However, they had little experience with ADs. Therefore, nurses' must develop both direct and indirect experience with ADs using a practical training program to strengthen their clinical competency regarding ADs.

Random Noise Addition for Detecting Adversarially Generated Image Dataset (임의의 잡음 신호 추가를 활용한 적대적으로 생성된 이미지 데이터셋 탐지 방안에 대한 연구)

  • Hwang, Jeonghwan;Yoon, Ji Won
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.12 no.6
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    • pp.629-635
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    • 2019
  • In Deep Learning models derivative is implemented by error back-propagation which enables the model to learn the error and update parameters. It can find the global (or local) optimal points of parameters even in the complex models taking advantage of a huge improvement in computing power. However, deliberately generated data points can 'fool' models and degrade the performance such as prediction accuracy. Not only these adversarial examples reduce the performance but also these examples are not easily detectable with human's eyes. In this work, we propose the method to detect adversarial datasets with random noise addition. We exploit the fact that when random noise is added, prediction accuracy of non-adversarial dataset remains almost unchanged, but that of adversarial dataset changes. We set attack methods (FGSM, Saliency Map) and noise level (0-19 with max pixel value 255) as independent variables and difference of prediction accuracy when noise was added as dependent variable in a simulation experiment. We have succeeded in extracting the threshold that separates non-adversarial and adversarial dataset. We detected the adversarial dataset using this threshold.

A Comparative Case Study on Sampling Methods for Cost-Effective Forest Inventory: Focused on Random, Systematic and Line Sampling (비용 효율적 표준지 조사를 위한 표본추출방법 비교 사례연구: 임의추출법, 계통추출법, 선상추출법을 중심으로)

  • Park, Joowon;Cho, Seungwan;Kim, Dong-geun;Jung, Geonhwi;Kim, Bomi;Woo, Heesung
    • Journal of Korean Society of Forest Science
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    • v.109 no.3
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    • pp.291-299
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    • 2020
  • The purpose of this study was to propose the most cost-effective sampling method, by analyzing the cost of forest resource investigation per sampling method for the planned harvesting area of in Chunyang-myeon, Byeonghwa-gun, Gyeongsangbuk-do, Korea. For this study, three sampling methods were selected: random sampling method, systematic sampling method, and line transect method. For each method, sample size, hourly wage, number of sample points, survey time, travel time, the sample error rate of the estimated average volume, and the desired sampling error rate were used to calculate the cost of forest resource inventories. Thus, 10 sampling points were extracted for each sampling method, and the factors required for cost analysis were calculated via a field survey. As a result, the field survey cost per ha using the random sampling method was found to be have the lowest cost, regardless of the desired sampling error rate, followed by the systematic sampling method, and the line transect method.

Matching Points Filtering Applied Panorama Image Processing Using SURF and RANSAC Algorithm (SURF와 RANSAC 알고리즘을 이용한 대응점 필터링 적용 파노라마 이미지 처리)

  • Kim, Jeongho;Kim, Daewon
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.4
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    • pp.144-159
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    • 2014
  • Techniques for making a single panoramic image using multiple pictures are widely studied in many areas such as computer vision, computer graphics, etc. The panorama image can be applied to various fields like virtual reality, robot vision areas which require wide-angled shots as an useful way to overcome the limitations such as picture-angle, resolutions, and internal informations of an image taken from a single camera. It is so much meaningful in a point that a panoramic image usually provides better immersion feeling than a plain image. Although there are many ways to build a panoramic image, most of them are using the way of extracting feature points and matching points of each images for making a single panoramic image. In addition, those methods use the RANSAC(RANdom SAmple Consensus) algorithm with matching points and the Homography matrix to transform the image. The SURF(Speeded Up Robust Features) algorithm which is used in this paper to extract featuring points uses an image's black and white informations and local spatial informations. The SURF is widely being used since it is very much robust at detecting image's size, view-point changes, and additionally, faster than the SIFT(Scale Invariant Features Transform) algorithm. The SURF has a shortcoming of making an error which results in decreasing the RANSAC algorithm's performance speed when extracting image's feature points. As a result, this may increase the CPU usage occupation rate. The error of detecting matching points may role as a critical reason for disqualifying panoramic image's accuracy and lucidity. In this paper, in order to minimize errors of extracting matching points, we used $3{\times}3$ region's RGB pixel values around the matching points' coordinates to perform intermediate filtering process for removing wrong matching points. We have also presented analysis and evaluation results relating to enhanced working speed for producing a panorama image, CPU usage rate, extracted matching points' decreasing rate and accuracy.

A novel ID-based multi-domain handover protocol for mesh points in WMNs

  • Zhang, Xue;Li, Guangsong;Han, Wenbao;Ji, Huifang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.7
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    • pp.2512-2529
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    • 2015
  • Wireless mesh networks (WMNs) provide an efficient and flexible method to the field of wireless networking, but also bring many security issues. A mesh point may lose all of its available links during its movement. Thus, the mesh point needs to handover to a new mesh point in order to obtain access to the network again. For multi-domain WMNs, we proposed a new ID-based signcryption scheme and accordingly present a novel ID-based handover protocol for mesh points. The mutual authentication and key establishment of two mesh points which belong to different trust domains can be achieved by using a single one-round message exchange during the authentication phase. The authentication server is not involved in our handover authentication protocol so that mutual authentication can be completed directly by the mesh points. Meanwhile, the data transmitted between the two mesh points can be carried by the authentication messages. Moreover, there are no restrictions on the PKG system parameters in our proposed multi-domain ID-based signcryption scheme so our handover scheme can be easily applied to real WMNs circumstances. Security of the signcryption scheme is proved in the random oracle model. It shows that our protocol satisfies the basic security requirements and is resistant to existing attacks based on the security of the signcryption. The analysis of the performance demonstrates that the protocol is efficient and suitable for the multi-domain WMNs environment.