A Two-Step Global Alignment Method for Feature-Based Image Mosaicing
نویسندگان
چکیده
منابع مشابه
A Two-Step Global Alignment Method for Feature-Based Image Mosaicing
Image mosaicing sits at the core of many optical mapping applications with mobile robotic platforms. As these platforms have been evolving rapidly and increasing their capabilities, the amount of data they are able to collect is increasing drastically. For this reason, the necessity for efficient methods to handle and process such big data has been rising from different scientific fields, where...
متن کاملA New Global Alignment Method for Feature Based Image Mosaicing
Over the past decade, image mosaicing has become as an important tool for several different areas such as panoramic photography, mapping, scene stabilization, video indexing and compression. Although recent advances in detection of image correspondences have resulted in very good image registration, global alignment is still needed to obtain a globally coherent mosaic. Normally, global alignmen...
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A feature based image mosaicing algorithm is presented in this project. A relaxation based correspondence algrithm is used to first select corresponding corners in two images. RANSAC is used to estimate the homography relating the two images. The estimated homogrphy is refined using Newton's non-linear method. A dynamic programming based blending algorithm was used to seamlessly blend the two i...
متن کاملFeature-Based Image Mosaicing
We propose an automatic image mosaicing method which can construct a panoramic image from a collection of digital still images. Our method is fast and robust enough to process a nonplanar scene with unrestricted camera motion. The method includes the following two techniques. First, we use a multiresolution patch-based optical flow estimation for making feature correspondences to obtain a homog...
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Machine learning is an application of artificial intelligence that is able to automatically learn and improve from experience without being explicitly programmed. The primary assumption for most of the machine learning algorithms is that the training set (source domain) and the test set (target domain) follow from the same probability distribution. However, in most of the real-world application...
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ژورنال
عنوان ژورنال: Mathematical and Computational Applications
سال: 2016
ISSN: 2297-8747
DOI: 10.3390/mca21030030