2018
DOI: 10.1109/access.2018.2882070
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Automatic Image Alignment Using Principal Component Analysis

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Cited by 27 publications
(21 citation statements)
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“…This drastically reduces the computational cost of alignment without compromising the correctness of alignment. Figure 5 shows the comparison of alignment obtained by our technique with that of [44]. We observe that the principal component directions in both cases are very similar.…”
Section: Alignment Using Pcamentioning
confidence: 88%
“…This drastically reduces the computational cost of alignment without compromising the correctness of alignment. Figure 5 shows the comparison of alignment obtained by our technique with that of [44]. We observe that the principal component directions in both cases are very similar.…”
Section: Alignment Using Pcamentioning
confidence: 88%
“…PAT stops at computing the aligned image and does not go further into analyzing if it is rotated or not, from a visual point of view. Some research [36] aims to correct such results by automatically assessing which of the two possible rotations represents the correct image. In case of images rotated to the left with large angles, PAT and EO may fail to provide the correct alignment.…”
Section: Monochrome Image Registrationmentioning
confidence: 99%
“…The methodology introduced in Section 3.5 has been applied on images belonging to Yale Face Database perturbed according to (36). The results are as follows.…”
Section: Monochrome Image Registration In Case Of Scaling On Multiple Dimensionsmentioning
confidence: 99%
“…It is done by a linear transformation of variables that leads to rotation and translation of the original coordinate system. PCA becomes a powerful tool to analyze the data and used to perform rotation compensation to rotate the stamp image [10,11]. Haar wavelet transform is the simplest wavelet transform variant.…”
Section: Introductionmentioning
confidence: 99%