• Title/Summary/Keyword: fractal feature

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Fast fractal coding based on LMSE analysis and subblock feature (LMSE 해석 및 부블록 특징에 근거한 고속 프랙탈 부호화)

  • 김상현;김남철
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.6
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    • pp.1279-1288
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    • 1997
  • In this paper, we propose a fast fractal coding method based on LMSE analysis and subblock feature. In the proposed method, scaling paarameter is calculated and whether search for each domain block should be done or not is determined based on the LMSE analysis of fractal approximation, and isometry parameter is chosen based on subblock feature. To investigate the efficiency of the proposed method, we compared it with Jacquin's method on image quality and encoding time. Experimental results show the proposed method yields nearly the same performance as that of Jacquin method in PSNR, and its encoding time is reduced by about 1/7 times.

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Evaluation of Chaotic evaluation of degradation signals of AISI 304 steel using the Attractor Analysis (어트랙터 해석을 이용한 AISI 304강 열화 신호의 카오스의 평가)

  • 오상균
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.9 no.2
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    • pp.45-51
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    • 2000
  • This study proposes that analysis and evaluation method of time series ultrasonic signal using the chaotic feature extrac-tion for degradation extent. Features extracted from time series data using the chaotic time series signal analyze quantitatively material degradation extent. For this purpose analysis objective in this study if fractal dimension lyapunov exponent and strange attractor on hyperspace. The lyapunov exponent is a measure of the rate at which nearby trajectories in phase space diverge. Chaotic trajectories have at least one positive lyapunov exponent. The fractal dimension appears as a metric space such as the phase space trajectory of a dynamical syste, In experiment fractal(correlation) dimensions and lyapunov experiments showed values of mean 3.837-4.211 and 0.054-0.078 in case of degradation material The proposed chaotic feature extraction in this study can enhances ultrasonic pattern recognition results from degrada-tion signals.

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Chaotic evaluation of material degradation time series signals of SA 508 Steel considering the hyperspace (초공간을 고려한 SA 508강의 재질열화 시계열 신호의 카오스성 평가)

  • 고준빈;윤인식;오상균;이영호
    • Journal of Welding and Joining
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    • v.16 no.6
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    • pp.86-96
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    • 1998
  • This study proposes the analysis method of time series ultrasonic signal using the chaotic feature extraction for degradation extent evaluation. Features extracted from time series data using the chaotic time series signal analyze quantitatively degradation extent. For this purpose, analysis objective in this study is fractal dimension, lyapunov exponent, strange attractor on hyperspace. The lyapunov exponent is a measure of the rate at which nearby trajectories in phase space diverge. Chaotic trajectories have at least one positive lyapunov exponent. The fractal dimension appears as a metric space such as the phase space trajectory of a dynamical system. In experiment, fractal correlation) dimensions, lyapunov exponents, energy variation showed values of 2.217∼2.411, 0.097∼ 0.146, 1.601∼1.476 voltage according to degardation extent. The proposed chaotic feature extraction in this study can enhances precision ate of degradation extent evaluation from degradation extent results of the degraded materials (SA508 CL.3)

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Vowel Recognition Using the Fractal Dimensioin (프랙탈 차원을 이용한 모음인식)

  • 최철영
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1994.06c
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    • pp.364-367
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    • 1994
  • In this paper, we carried out some experiments on the Korean vowel recognition using the fractal dimension of the speech signals. We chose the Mincowski-Bouligand dimensioni as the fractal dimension, and computed it using the morphological covering method. For our experiments, we used both the fractal dimension and the LPC cepstrum which is conventionally known to be one of the best parameters for speech recognition, and examined the usefulness of the fractal dimension. From the vowel recognition experiments under various consonant contexts, we achieved the vowel recognition error rats of 5.6% and 3.2% for the case with only LPC cepstrum and that with both LPC cepstrum and the fractal dimension, respectively. The results indicate that the incorporation of the fractal dimension with LPC cepstrum gies more than 40% reduction in recognition errors, and indicates that the fractal dimension is a useful feature parameter for speech recognition.

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Design of FRACTAL Image Compression Decoder (FRACTAL 영상 압축 Decoder 설계)

  • 김용배;박형근;임순자;김용환
    • Proceedings of the IEEK Conference
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    • 1999.06a
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    • pp.623-626
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    • 1999
  • As the information society is advanced, the needs for mass information storage and retrieval grows. Digital image information is stored in retrieval systems, broadcasting in television transmission and exchanged over several kinds of telecommunication media. A major problem is that digital images are represented with large amount of data. The useful feature of image compression is that transmitting rapidly a lot of data in less time. Therefore we proposed a parallel Fractal trans-formation unit in Fractal Image compression system.

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Transient Stability Analysis Using Fractal Behaviours (프랙탑 현상을 이용한 과도 안정도 해석)

  • Choi, Jong-Yun;Ahn, Hyun-Sik;Kim, Jin-O
    • Proceedings of the KIEE Conference
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    • 1997.07c
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    • pp.1103-1105
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    • 1997
  • Transient stability analysis is concerned with a power system's response to unwanted disturbance. Recently, direct method which utilize the stable region of stable equilibrium point is used to analyze transient stability This paper focuses on the controlling UEP method using the fractal behaviours. In the controlling UEP method, many algorithms are used to find controlling UEP However, the existence of fractal region gives difficulty in finding the controlling UEP. So, this paper observes the fractal feature arid introduce the fractal index to explain how much the fractal region occupies in the entire space. Using an improved algorithm from the view point of fractal index, we are going to find the controlling UEP.

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Resolution-independent Up-sampling for Depth Map Using Fractal Transforms

  • Liu, Meiqin;Zhao, Yao;Lin, Chunyu;Bai, Huihui;Yao, Chao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.6
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    • pp.2730-2747
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    • 2016
  • Due to the limitation of the bandwidth resource and capture resolution of depth cameras, low resolution depth maps should be up-sampled to high resolution so that they can correspond to their texture images. In this paper, a novel depth map up-sampling algorithm is proposed by exploiting the fractal internal self-referential feature. Fractal parameters which are extracted from a depth map, describe the internal self-referential feature of the depth map, do not introduce inherent scale and just retain the relational information of the depth map, i.e., fractal transforms provide a resolution-independent description for depth maps and could up-sample depth maps to an arbitrary high resolution. Then, an enhancement method is also proposed to further improve the performance of the up-sampled depth map. The experimental results demonstrate that better quality of synthesized views is achieved both on objective and subjective performance. Most important of all, arbitrary resolution depth maps can be obtained with the aid of the proposed scheme.

Printed Numeric Character Recognition using Fractal Dimension and Modified Henon Attractor (프랙탈 차원과 수정된 에농 어트랙터를 이용한 인쇄체 숫자인식)

  • 손영우
    • Journal of Korea Multimedia Society
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    • v.6 no.1
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    • pp.89-96
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    • 2003
  • This paper propose the new method witch is adopted in extracting character features and recognizing numeric characters using fractal dimension and modified Henon Attractor of the Chaos Theory. Firstly, it gets features of mesh feature, projection feature and cross distance feature from numeric character images And their feature hi converted into time series data. Then using the modified Henon system suggested in this paper, it gets last features of numeric character image after calculating Natural Measure and information bit which art meant fractal dimension. Finally, numeric character recognition is performed by statistically finding out the each information bit showing the minimum difference against the normalized pattern database. An Experimental result shows 100% character classification rates for 10 digits and 90% of recognition rates in real situation and the recognition speed was 26 characters per second.

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Construction fo chaos simulator for ultrasonic pattern recognition evaluation of weld zone in austenitic stainless steel 304 (오스테나이트계 스테인리스강 304 용접부의 초음파 형상 인식 평가를 위한 카오스 시뮬레이터의 구축)

  • Yi, Won;Yun, In-Sik;Chang, Young-Kwon
    • Journal of Welding and Joining
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    • v.16 no.5
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    • pp.108-118
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    • 1998
  • This study proposes th analysis and evaluation method of time series ultrasonic signal using the chaos feature extraction for ultrasonic pattern recognition. Features extracted from time series data using the chaos time series signal analyze quantitatively weld defects. For this purpose, analysis objective in this study is fractal dimension and Lyapunov exponent. Trajectory changes in the strange attractor indicated that even same type of defects carried substantial difference in chaosity resulting from distance shifts such as 0.5 and 1.0 skip distance. Such differences in chaosity enables the evaluation of unique features of defects in the weld zone. In quantitative chaos feature extraction, feature values of 4.511 and 0.091 in the case of side hole and 4.539 and 0.115 in the case of vertical hole were proposed on the basis of fractal dimension and Lyapunov exponent. Proposed chaos feature extraction in this study can enhances ultrasonic pattern recognition results from defect signals of weld zone such as side hole and vertical hole.

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Fractal Feature Extraction

  • Jay Feng;Lin, Wei-Chung;Rhee, Sang-Yong;Park, Jae-Yun
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.624-627
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    • 2003
  • To achieve accurate and efficient extraction of the fractal feature, a progressive extraction method is developed. After establishing the boundaries of the targeted surface by enclosing it with internal and external covers, it determines the features of the surface by calculating the characteristics of such covers.

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