Analysis of operators for detection of corners set in automatic image matching

• Autorzy: Zawieska D.
• Języki publikacji: EN

Abstrakty

EN

Reconstruction of three dimensional models of objects from images has been a long lasting research topic in photogrammetry and computer vision. The demand for 3D models is continuously increasing in such fields as cultural heritage, computer graphics, robotics and many others. The number and types of features of a 3D model are highly dependent on the use of the models, and can be very variable in terms of accuracy and time for their creation. In last years, both computer vision and photogrammetric communities have approached the reconstruction problems by using different methods to solve the same tasks, such as camera calibration, orientation, object reconstruction and modelling. The terminology which is used for addressing the particular task in both disciplines is sometimes diverse. On the other hand, the integration of methods and algorithms coming from them can be used to improve both. The image based modelling of an object has been defined as a complete process that starts with image acquisition and ends with an interactive 3D virtual model. The photogrammetric approach to create 3D models involves the followings steps: image pre-processing, camera calibration, orientation of images network, image scanning for point detection, surface measurement and point triangulation, blunder detection and statistical filtering, mesh generation and texturing, visualization and analysis. Currently there is no single software package available that allows for each of those steps to be executed within the same environment. For high accuracy of 3D objects reconstruction operators are required as a preliminary step in the surface measurement process, to find the features that serve as suitable points when matching across multiple images. Operators are the algorithms which detect the features of interest in an image, such as corners, edges or regions. This paper reports on the first phase of research on the generation of high accuracy 3D model measurement and modelling, focusing upon the application of different operators for accurate feature point extraction. The implementation of those operators is discussed and performance of differen operators is analysed. The optimal operator for high accuracy close range object reconstruction is then highlighted. This research has facilitated a development of the feature extraction and image measurement process that will be central to the development of an automatic procedure for high accuracy point cloud generation in multi image networks where robust orientation and 3D point determination will facilitate surface measurement and modelling within a single software system.

Słowa kluczowe

EN

feature detection; corner detection; 3D modelling; image matching

PL

funkcja wykrywania; wykrywanie krawędzi; modelowanie 3D; dopasowanie obrazów

• Wydawca: Zarząd Główny Stowarzyszenia Geodetów Polskich
• Czasopismo: Archiwum Fotogrametrii, Kartografii i Teledetekcji
• Rocznik: 2011
• Tom: Vol. 22
• Strony: 423--436
• Opis fizyczny: Bibliogr. 7 poz.

Twórcy

autor

Zawieska D.

• Department of Photogrammetry Remote Sensing and Spatial Information Systems Faculty of Geodesy and Cartography, Warsaw University of Technology Pl. Politechniki 1, 00-661 Warszawa, Poland

Bibliografia

• Harris C., and M.J. Stephens (1988). ;”A combined corner and edge detector”. In Alvey Vision Conference, pages 147–152. 8.
• Jun Jie Liu. A. Jakas. A. Al-Obaidi. Yonghuai Liu A., (2009). “Comparative study of Different corner detection methods in Computational Intelligence in Robotics and Automation (CIRA)”. IEEE International Symposium, pages 509 – 514.
• Lang F, Förstner, W., (1998).” Matching Techniques, Third Course in Digital Photogrammetry”,
• Moravec H.P ,(1977).:” Towards Automatic Visual Obstacle Avoidance”. Proc. 5th International Joint Conference on Artificial Intelligence, pp. 584.
• Remondino F., (2003).: ”From point cloud to surface: The modelling and visualization Problem”. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXIV-5/W10
• Smith S.,M and J.M. Brady (1997).: “ SUSAN - a new approach to low level image Processing”. International Journal of Computer Vision. 23(1):45-78.
• Zawieska D., (2010).: „ Selected operators in automation of matching close-range digital Images”, Arch. Photogrammetry, Cartography and Remote Sensing, Vol. XXI., pages 455 - 465.