A robust video text detection approach using SVM
Expert Systems with Applications: An International Journal
| Hi-index | 0.00 |
In this paper, we propose a simple yet powerful video text location scheme. Firstly, an edge-based background classification is applied to the input video frames, which are subsequently classified into three categories: simple, normal and complex. Then, for the three different types of video frames, different text location methods are adopted, respectively: for the simple background class, a stroke-based text location scheme is used; for the normal background class, a variant of morphology called conditional morphology is incorporated to remove the non-text noises; for the complex background situation, after location routine based on stroke analysis and conditional morphology, an SVM text detector is trained to reduce the false alarms. Experimental results show that our approach performs well in various videos with high speed and precision.