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Speeded Up Robust Features (SURF) is one of the most robust and widely used image matching algorithms based on local features. However, the performance for rotation image is poor when one image is a rotated version of the other. To improve the matching accuracy of rotation image, we present an modified image matching algorithm combining Haar wavelet and the rotation invariant Local Binary Patterns...
In the field of nanotechnology, tracking freely swimming microorganisms under a microscope is difficult. An image of the target often rotates and changes shape as it moves. Further, the difficulty increases with background changes and fluctuations of colors and the brightness because of differences in the surrounding environment. To address these problems, we propose a tracking method combined with...
Local image features have been designed to be informative and repeatable under rigid transformations and illumination deformations. Even though current state-of-the-art local image features present a high degree of repeatability, their local appearance alone usually does not bring enough discriminative power to support a reliable matching, resulting in a relatively high number of mismatches in the...
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