In the paper, a novel hybrid method for an automatic quality assessment of binary images is proposed that may be useful, e.g., for computationally limited embedded systems or Optical Character Recognition applications. Since the quality of binary images used as the input for further image analysis strongly influences the obtained results, a reliable evaluation of their quality is a crucial element for the validation of such...

In the paper a method supporting the optical character recognition from video sequences recorded with cameras without good stabilization is proposed. Due to the presence of various distortions, such as motion blur, shadows, lossy compression artifacts, auto-focusing errors, etc., the quality of individual video frames, e.g., recorded by a smartphone camera, differs noticeably, influencing the results of text recognition, causing...

In the paper the idea of the combined image quality metric based on the structural and feature similarity comparison is discussed. Since most of image quality assessment methods developed during last years require the nonlinear mapping to obtain high correlation with subjective quality scores, there is an important problem of choosing the proper mapping function and its optimal parameters in practical applications. The most...