Scene Text Extraction in IHLS Color Space Using Support Vector Machine

Scene text extraction is challenging research area due to variety of image degradations caused by imaging conditions and low cost consumer devices. In this paper we propose text extraction method that uses chroma and lightness component for generation of extraction hypotheses and incorporates SVM (support vector machine) based text detection stage as tool for hypotheses verification. Choice of chroma and lightness components is based on their complementarity with respect to image degradations like shadows and highlights. Another novelty is usage of IHLS color space for text extraction task which is motivated by saturation definition that eliminates instability of this component at low lightness values. Results obtained on the ICDAR 2011 dataset confirm complementarity of chroma and lightness. Compared to the state-of-the-art methods proposed algorithm achieves higher correct recognition rate and comparable total edit distance. DOI: http://dx.doi.org/10.5755/j01.itc.44.1.5757