An In-Depth Analysis On Image Mosaicing Methodologies | | Posted on:2020-04-14 | Degree:Master | Type:Thesis | | Institution:University | Candidate:MOHAMED ABDUL-RAHIM MASOUD ISS | Full Text:PDF | | GTID:2428330572467391 | Subject:Computer Science and Technology | | Abstract/Summary: | PDF Full Text Request | | Image mosaicing is one of the most important subjects of research in computer vision at current.Image mocaicing requires the integration of direct techniques and feature based techniques.Direct techniques are found to be very useful for mosaicing large overlapping regions,small translations and rotations while feature based techniques are usenil for small overlapping regions.Feature based image mosaicing is a combination of comer detection,comer matching,motion parameters estimation and image stitching.In addition to the above,image mosicing in real time applications continues to be a challenging field for experts in this field.The research area has a wide application in the field of 3-dimention image reconstruction,video conferencing,numerous medical and computer vision areas as well as satellite imaging.There are four commonly known steps involved in feature-based techniques,all identified as primary steps which include feature detection,feature matching,transformation model estimation,image resampling as well as transformation.Scale Invariant Feature Transformation(SIFT)-based feature detector and Speeded Up Robust Feature(SURF)-based feature detector are both algorithms which are based on feature detection in order to accomplish image mosaicing,however both the two algorithms have strengths and limitations of their own in terms on their application.In this thesis the author analyses and proposes techniques which are employed by both the above mentioned image mosaicing methods in order to generate an output image that is a result of the limitations in reference to the image quality.In this course of this thesis,the author classifies the past and current mosaicing techniques based on image registration as well as image blending.For each of these classifications,the author provides a comprehensive review of the major categories of the image mosaicing methods.The basics of these categories are first described.Then,for each of these basic categories,the evolving paths are discussed by providing the modifications that have been applied to the basic methods by different researchers and review papers.Since the current state-of-the-art is broad,only those works,which the author believed and thought contributed significantly to the mosaicing literature,are discussed in this research. | | Keywords/Search Tags: | Image mosaicing, Registration, Blending, Geometric transformation, Homography, Low-level feature, Transition smoothening, Optimal seam, Feature extraction | PDF Full Text Request | Related items |
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