Performance Comparison of Cosine, Haar, Walsh-hadamard, Fourier and Wavelet Transform for Shape based Image Retrieval Using Fuzzy Similarity Measure

Banerjee, Alina; Dutta, Ambar

doi:10.1016/j.protcy.2013.12.403

Cited by 8 publications

(3 citation statements)

References 3 publications

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“…In addition, Humberto et al estimated the non-subsampled Haar wavelet coefficients by using a linear estimator for high-resolution small animal 3D positron emission tomography (PET) data fusion [26]. Furthermore, the fractional Fourier (FRT) and linear canonical transforms (LCT) [27], and Walsh-hadamard transform [28] have been developed based on Haar wavelet transform. Consequently, the current work applied wavelet basis functions of haar for plantar pressure image fusion operation.…”

Section: Introductionmentioning

confidence: 99%

Diabetic plantar pressure analysis using image fusion

Cao

Dey

Ashour

et al. 2018

Multimed Tools Appl

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Plantar pressure images analysis is the key issue of designing comfortable shoe products through last customizing system, which has attracted the researchers' curiosity toward image fusion as an application of medical and industrial imaging. In the current work, image fusion has been applied using wavelet transform and compared with Laplace Pyramid. Using image fusion rules of Mean-Max, we presented a plantar pressure image fusion method employing haar wavelet transform. It was compared in different composition layers with the Laplace pyramid transform. The experimental studies deployed the haar, db2, sym4, coif2, and bior5.5 wavelet basis functions for image fusion under decomposition layers of 3, 4, and 5. Evaluation metrics were measured in the case of the different layer number of wavelet decomposition to determine the best decomposition level and to evaluate the fused image quality using with different wavelet functions. The best wavelet basis function and decomposition layers were selected through the analysis and the evaluation measurements. This study established that haar wavelet transform with five decomposition levels on plantar pressure image achieved superior performance of 89.2817% mean, 89.4913% standard deviation, 5.4196 average gradient, 14.3364 spatial frequency, 5.9323 information entropy and 0.2206 cross entropy.

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Section: Introductionmentioning

confidence: 99%

Diabetic plantar pressure analysis using image fusion

Cao

Dey

Ashour

et al. 2018

Multimed Tools Appl

View full text Add to dashboard Cite

show abstract

“…The color and texture information in the locations given by these points provides significantly improved results in terms of retrieval accuracy, computational complexity and storage space of feature vectors as compared to the global feature approaches. A performance comparison is done on various image transforms like Wavelet transform, Fourier transform, Haar transform, Walsh-Hadamard transform and discrete cosine transform using a fuzzy similarity measure is presented in [5,6]. It is seen that according to retrieval performance Wavelet transform gives the best result among the other mentioned transforms.…”

Section: Introductionmentioning

confidence: 99%

Orientation Spectral Resolution Coding for Pattern Recognition

Muneeruddin¹,

Patil²

2017

IOSR JCE

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“…Commonly used orthogonal transforms include discrete cosine transform (DCT), Fourier transform, wavelet transform, Laplace transform, Walsh transform, etc. [1][2][3][4][5] . As a global transform, DCT cannot be effective on the recognition of local features.…”

Section: Introductionmentioning

confidence: 99%

Robust Approach for minimizing size of transmitted sound signal using Walsh–Hadamard transform

2017

IJMTER

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In this paper, a new approach of compressing sound signal based on the Walsh-Hadamard transform has been proposed. The compression issue is performed by considering limited interval in the transformed plane of the sound signal as a transmission data based on the knowledge that most of the energy of the signal is focused on high coefficients area of the Walsh-Hadamard transform. Consequently, on the receive side the sound signal is reconstructed using the inverse Walsh-Hadamard transform. The missing part of the transformed spectrum will be compensated with a calculated value for all coefficients in the missing part. The reconstructed sound signal is evaluated with the original sound signal using the standard metrics of signal accuracy. The simulation results from the proposed approach view significant percent of accuracy for the reconstructed signal.

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Performance Comparison of Cosine, Haar, Walsh-hadamard, Fourier and Wavelet Transform for Shape based Image Retrieval Using Fuzzy Similarity Measure

Cited by 8 publications

References 3 publications

Diabetic plantar pressure analysis using image fusion

Diabetic plantar pressure analysis using image fusion

Orientation Spectral Resolution Coding for Pattern Recognition

Robust Approach for minimizing size of transmitted sound signal using Walsh–Hadamard transform

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