An Automatic Performance Evaluation Protocol for Video Text Detection Algorithms

Text presented in the videos provides important supplemental information for video indexing and retrieval. Many efforts have been made for text detection in videos. However, there is still lack of performance evaluation protocols for video text detection. In this paper, we propose an objective and comprehensive performance evaluation protocol for video text detection algorithms. The protocol includes a positive set and a negative set of indices at textbox level, which evaluate the detection quality in terms of both location accuracy and fragmentation of the detected textboxes. In the protocol, we assign a detection difficulty (DD) level to each ground truth textbox. The performance indices can then be normalized with respect to the textbox DD level and are therefore tolerant to different ground-truth difficulty to a certain degree. We also assign a detectability index (DI) value to each ground truth textbox. The overall detection rate is the DI-weighted average of the detection qualities of all ground truth textboxes, which makes the detection rate more accurate to reveal the real performance. The automatic performance evaluation scheme has been applied to performance evaluation of a text detection approach to determine its best thresholds that can yield the best detection results. The protocol has also been employed to compare the performances of several text detection systems. Hence, we believe that the proposed protocol can be used to compare the performance of different video/image text detection algorithms/systems, and can even help improve, select, and design new text detection methods.