An Efficient Weld Image Classification System Using Wavelet And Support Vector Machine

Kalaiselvi, V.K.G.; Aravindhar, D. John

doi:10.1109/iccct2.2019.8824884

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A Wt Decomposition1

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2019

2023

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Cited by 2 publications

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“…WT uses the fourier and real space. WT is also used in object recognition [11], brain image classification [12] and weld image classification [13]. It returns the data vector with the same input length.…”

Section: A Wt Decompositionmentioning

confidence: 99%

Wavelet Transform Based CT and PET Lung Image Fusion

Devi¹

2019

IJEAT

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The lung cancer reduces the breathing ability and it causes due to uncontrollable cells in the lungs. The fusion of Computed Tomography (CT) and Positron Emission Tomography (PET) has clear information about lungs comparing with individual CT and PET images. The fused image helps to find cancer in a starting stage. In this study, a novel method for fusion of CT and PET lung images using Wavelet Transform (WT) and MaxMin (MM) rule is presented. Initially, the CT and PET lung images are decomposed by WT. The subband coefficients of WT are extracted by using entropy features. Then MM rule is applied, after that the image is reconstructed to form the fused lung image. The performance is evaluated by Reference Image Database to Evaluate therapy Response (RIDER) lung database. Results and discussion shows the performance of Lung Image Fusion (LIF).

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Section: A Wt Decompositionmentioning

confidence: 99%