In this paper we present a binarization technique for textual content in
video frames which can be applied in the resulting image of the text
detection step aiming in an improved OCR performance. The proposed
technique is based on the detection of the text baselines in order to
define the main body of the text. The main body of the text is used to
detect the stroke width of the characters which will address the two
consecutive locally adaptive binarization steps that follow. At the
first step, we use different valuation in parameters for the inside and
outside area of the main body of the text. To include the thinned or
broken binarized parts that may exist outside the main text body, convex
hull analysis is performed so that the entire text body is considered.
At the second step, binarization is performed with different valuation
in parameters for the inside and outside area of the entire text body.
The effectiveness of the proposed technique is demonstrated by both
qualitative and OCR-based evaluation