Feature detection and fusion for intelligent compression

Ducksbury, Paul G.; Varga, Margaret

doi:10.1049/ic:20010106

Cited by 4 publications

(4 citation statements)

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“…Higher the irregularity of a dynamic response of a given system, higher the entropy values are. Evaluation of complexity values of time-series data based on entropy measures are well studied in different disciplines including biomedical studies [44,45], in characterizing human motion [46], image processing [47,48], in financial market studies [49] and so on. [24].…”

Section: Organization Of the Thesismentioning

confidence: 99%

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Identification of breathing cracks in a beam structure with entropy

Wimarshana

2016

SPIE Proceedings

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During vibration of engineering structures, fatigue cracks may exhibit repetitive crack open-close breathing like phenomenon which ultimately result in a distinct crack type, breathing cracks.This breathing phenomenon generates bi-linearity and irregularities in vibration signals of the cracked structure which carry useful information about the crack occurrence. In this thesis, the concept of entropy is employed to quantify this bi-linearity/irregularity of the vibration response so as to evaluate crack severity. To increase the sensitivity of the entropy calculation to detect the damage severity, sample entropy and quantized approximation of sample entropy are merged with wavelet transformation (WT) which is capable of amplifying the weak irregularities in vibration signal caused by small and initial breathing cracks. A cantilever beam with a breathing crack is studied to asses proposed crack identification method under two vibration conditions with sinusoidal and random excitations. An iterative numerical model is established to generate accurate time domain vibration responses of the cantilever with a breathing crack. Through both numerical simulations and experimental testing, the breathing crack identification with entropy under sinusoidal excitation is studied first and proven to be effective. Then, the crack identification sensitivity under lower excitation frequencies is further improved by parametric optimization of sample entropy and WT. Finally, effective breathing crack identification under general random excitations are experimentally studied and realized using frequency response functions (FRFs) which adapts the proposed crack identification technique to the incurred extra complexity due to random nature of the excitation and structural response.iii

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Section: Organization Of the Thesismentioning

confidence: 99%

“…, ( )} , then relative coarse quantization of the time series is performed using a strictly positive parameter , which defines the size of the quantization bins [48]. Then the quantized time series is:…”

Section: Quantized Approximation Of Sample Entropy (Qase)mentioning

confidence: 99%

Identification of breathing cracks in a beam structure with entropy

Wimarshana

2016

SPIE Proceedings

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“…An annotation tool was developed to provide the facilities for the clinicians to graphically annotate the areas of diagnostic interest or concern by drawing an ellipse around them and entering a corresponding descriptive text input if required. Both the graphical and textual annotations are an overlay to the image, figure 3 shows an annotated microscopic tile image [9].…”

Section: Annotationmentioning

confidence: 99%

<title>Application of content-based image compression to telepathology</title>

Varga

Ducksbury

Callagy

2002

Medical Imaging 2002: Visualization, Image-Guided Procedures, and Display

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Telepathology is a means of practicing pathology at a distance, viewing images on a computer display rather than directly through a microscope. Without compression, images take too long to transmit to a remote location and are very expensive to store for future examination. However, to date the use of compressed images in pathology remains controversial. This is because commercial image compression algorithms such as JPEG achieve data compression without knowledge of the diagnostic content. Often images are lossily compressed at the expense of corrupting informative content.None of the currently available lossy compression techniques are concerned with what information has been preserved and what data has been discarded. Their sole objective is to compress and transmit the images as fast as possible. By contrast, this paper presents a novel image compression technique, which exploits knowledge of the slide diagnostic content. This 'content based' approach combines visually lossless and lossy compression techniques, judiciously applying each in the appropriate context across an image so as to maintain 'diagnostic' information while still maximising the possible compression. Standard compression algorithms, e.g. wavelets, can still be used, but their use in a context sensitive manner can offer high compression ratios and preservation of diagnostically important information. When compared with lossless compression the novel content-based approach can potentially provide the same degree of information with a smaller amount of data. When compared with lossy compression it can provide more information for a given amount of compression. The precise gain in the compression performance depends on the application (e.g. database archive or second opinion consultation) and the diagnostic content of the images.

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“…34 Higher the complexity of a dynamic response of a given system, higher the entropy values are. Evaluation of complexity values of time series data based on entropy measures are well studied in different disciplines including biomedical studies, 35,36 in characterizing human motion, 37 image processing, 38,39 in financial market studies, 40 and so on. In the damage detection perspective, in the recent studies, various entropy measures are being applied in rotary machines to diagnose various damages.…”

Section: Introductionmentioning

confidence: 99%

Application of entropy in identification of breathing cracks in a beam structure: Simulations and experimental studies

Wimarshana

2017

Structural Health Monitoring

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A cantilever beam with a breathing crack is studied to detect the crack and evaluate the crack depth using entropy measures. During the vibration in engineering structures, fatigue cracks undergo the status from close-to-open (and open-to-close) repetitively leading to a crack breathing phenomenon. Entropy is a measure, which can quantify the complexity or irregularity in system dynamics, and hence employed to quantify the bi-linearity/irregularity of the vibration response, which is induced by the breathing phenomenon of a crack. A mathematical model of harmonically excited unit length steel cantilever beam with a breathing crack located near the fixed end is established, and an iterative numerical method is applied to generate accurate time domain vibration responses. The steady-state time domain vibration signals are pre-processed with wavelet transformation, and the bi-linearity/irregularity of the vibration signals due to breathing effect is then successfully quantified using both sample entropy and quantized approximation of sample entropy to detect and estimate the crack depth. It is observed that the method is capable of identifying crack depths even at very early stages of 3% of the beam thickness with significant increment in the entropy values (more than 200%) compared to the healthy beam. In addition, experimental studies are conducted, and the simulation results are in good agreement with the experimental results. The proposed technique can also be applied to damage identification in other types of structures, such as plates and shells.

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Feature detection and fusion for intelligent compression

Cited by 4 publications

References 0 publications

Identification of breathing cracks in a beam structure with entropy

Identification of breathing cracks in a beam structure with entropy

<title>Application of content-based image compression to telepathology</title>

Application of entropy in identification of breathing cracks in a beam structure: Simulations and experimental studies

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