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Map Quality Assessment



Asim Wagan, Afzal A. Godil, Xiaolan Li


The Maps captured by robots in real environment are usually incomplete, distorted, and noisy. To evaluate the quality of these kind of maps is an important problem in the field. In this paper we present an algorithm to assess the quality of the map generated by the robot. First, localized features are calculated on the pre-evaluated map. Second, nearest neighbor of each valid local feature is searched between the map and the ground truth map. The quality of the map is defined according to the number of the features having the correspondence in the ground truth map. Three feature detectors are used, which are the Harris corner detector, Hough Transform and Scale Invariant Feature Transform
Conference Dates
August 19-21, 2008
Conference Location
Gaithersburg, MD
Conference Title
Performance Metrics for Intelligent Systems Workshop Proceedings (PerMIS)


feature detector, Harris corner detector, Hough transform, image quality, map quality, SIFT


Wagan, A. , Godil, A. and Li, X. (2008), Map Quality Assessment, Performance Metrics for Intelligent Systems Workshop Proceedings (PerMIS), Gaithersburg, MD, [online], (Accessed April 25, 2024)
Created August 19, 2008, Updated February 19, 2017