caa a22 4500 467884242 CHVBK 20180406152729.0 cr unu---uuuuu 170328e20060901xx s 000 0 eng 10.1007/s10032-006-0014-0 doi (NATIONALLICENCE)springer-10.1007/s10032-006-0014-0 Object count/area graphs for the evaluation of object detection and segmentation algorithms [Elektronische Daten] [Christian Wolf, Jean-Michel Jolion] Evaluation of object detection algorithms is a non-trivial task: a detection result is usually evaluated by comparing the bounding box of the detected object with the bounding box of the ground truth object. The commonly used precision and recall measures are computed from the overlap area of these two rectangles. However, these measures have several drawbacks: they don't give intuitive information about the proportion of the correctly detected objects and the number of false alarms, and they cannot be accumulated across multiple images without creating ambiguity in their interpretation. Furthermore, quantitative and qualitative evaluation is often mixed resulting in ambiguous measures. In this paper we propose a new approach which tackles these problems. The performance of a detection algorithm is illustrated intuitively by performance graphs which present object level precision and recall depending on constraints on detection quality. In order to compare different detection algorithms, a representative single performance value is computed from the graphs. The influence of the test database on the detection performance is illustrated by performance/generality graphs. The evaluation method can be applied to different types of object detection algorithms. It has been tested on different text detection algorithms, among which are the participants of the ICDAR 2003 text detection competition. Springer-Verlag, 2006 Evaluation nationallicence Object detection nationallicence Text detection nationallicence Wolf Christian LIRIS-INSA de Lyon, Bât. Jules Verne, 20, Avenue Albert Einstein, 69621, Villeurbanne cedex, France aut Jolion Jean-Michel LIRIS-INSA de Lyon, Bât. Jules Verne, 20, Avenue Albert Einstein, 69621, Villeurbanne cedex, France aut International Journal of Document Analysis and Recognition (IJDAR) Springer-Verlag 8/4(2006-09-01), 280-296 1433-2833 8:4<280 2006 8 10032 https://doi.org/10.1007/s10032-006-0014-0 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10032-006-0014-0 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Wolf Christian LIRIS-INSA de Lyon, Bât. Jules Verne, 20, Avenue Albert Einstein, 69621, Villeurbanne cedex, France aut NATIONALLICENCE 700 1- Jolion Jean-Michel LIRIS-INSA de Lyon, Bât. Jules Verne, 20, Avenue Albert Einstein, 69621, Villeurbanne cedex, France aut NATIONALLICENCE 773 0- International Journal of Document Analysis and Recognition (IJDAR) Springer-Verlag 8/4(2006-09-01), 280-296 1433-2833 8:4<280 2006 8 10032 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer