Performance Evaluation of Real-time and Scale-invariant LoG Operators for Text Detection

This paper presents a state-of-the-art and a performance evaluation of real-time text detection methods, having particular focus on the family of Laplacian of Gaussian (LoG) operators with scale-invariance. The computational complexity of operators is discussed and an adaptation to text detection is obtained through the scale-space representation. In addition, a groundtruthing process and a characterization protocol are proposed, performance evaluation is driven with repeatability and processing time. The evaluation highlights a near-exact approximation with real-time operators at one to two orders of magnitude of execution time. The real-time operators are adapted to recent camera devices to process high resolution images. Perspectives are provided for operator robustness, optimization and characterization of the detection strategy.