<p>In robot navigation, and image content searches reliable salient features are of pivotal importance. Also in biometric human recognition, salient features are increasingly used. </p><p>Regardless the application, image matching is one of the many problems in computer </p><p>vision, including object recognition. </p><p> </p><p>This report investigates some salient features to match sub-images of different images. </p><p>An underlying assumption is that sub-images, also called image objects, or objects, are </p><p>possible to recognize by the salient features that can be recognized independently. </p><p> </p><p>Since image objects are images of 3D objects, the salient features in 2D images must be </p><p>invariant to reasonably large viewing direction and distance (scale) changes. These </p><p>changes are typically due to 3D rotations and translations of the 3D object with respect to </p><p>the camera. Other changes that influence the matching of two 2D image objects is </p><p>illumination changes, and image acquisition noise. </p><p> </p><p>This thesis will discuss how to find the salient features and will compare them with </p><p>respect to their matching performance. Also it will explore how these features are </p><p>invariant to rotation and scaling.</p>
| Identifer | oai:union.ndltd.org:UPSALLA/oai:DiVA.org:hh-1145 |
| Date | January 2008 |
| Creators | Farzaneh, Sara |
| Publisher | Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Högskolan i Halmstad/Sektionen för Informationsvetenskap, Data- och Elektroteknik (IDE) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, text |
Page generated in 0.002 seconds