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By choosing a suitable encoding system these vectors are largely invariant with respect to the view orientation and can thus be compared between images based on Euclidean distance.
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Most reconstruction-based methods perform registration between LR images based on their motions, followed by restoration for blur and noise removal.
A simple and robust algorithm was proposed to determine the rotational differences between two images based on orientation histogram matching accumulated from local orientation of each pixel without any feature extraction.
This paper proposes a deep learning based framework for heterogeneous iris verification, namely DeepIris, which learns relational features to measure the similarity between pairs of iris images based on convolutional neural networks.
Koh et al 25 were the first to apply original algorithms to automatically analyse meibography images to identify meibomian glands, and showed a clear distinction between healthy and unhealthy images based on both the mean arc length and mean entropy.
Fang et al. [21] proposed a visual attention model for stereoscopic images based on the contrast between low-level features.
Contours were drawn on the T2-weighted images, based on image pixel intensities.
Consider grouping images based on colors.
The hierarchy segments an image based on distance between colors and stores the pixel values in separated branches.
First, we present improved adaptive LSB steganography that can embed messages adaptively and thus can satisfy various requirements (high capacity, high security, high image quality, etc).. Second, our method minimizes degradation of the stego image through finding the best mapping between the secret message and the cover image based on chaos and the genetic algorithm (GA).
During recognition, we match the probe and gallery image based on the relative change of stable pixels between image pairs.
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