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Research Article Open Access
This paper presents the review of feature detection techniques for image mosaicing which is an important research subject in the field of computer vision. Image mosaicing is the process of combining several overlapped images to create single continuous image. Feature extraction methods extract the distinct features from the images like edges, corners, etc. which can be used to match the similarity for estimation of relative transformation between the images. Features based methods have shown much advantage over direct mosaicing methods in both time and space complexity. Thus large number of research has been done around the feature extraction and feature matching algorithms to improve processing of algorithm execution in terms of speed and space. Here we discussed some techniques which are commonly used for the image mosaicing.
Image registration, Feature extraction, Image blending, Image mosaicing, FAST, SIFT, SURF, PCA-SIFT., Extraction Chromatography