摘要
Natural scene recognition has important significance and value in the fields of image retrieval,autonomous navigation,human-computer interaction and industrial automation.Firstly,the natural scene image non-text content takes up relatively high proportion;secondly,the natural scene images have a cluttered background and complex lighting conditions,angle,font and color.Therefore,how to extract text extreme regions efficiently from complex and varied natural scene images plays an important role in natural scene image text recognition.In this paper,a Text extremum region Extraction algorithm based on Joint-Channels(TEJC)is proposed.On the one hand,it can solve the problem that the maximum stable extremum region(MSER)algorithm is only suitable for gray images and difficult to process color images.On the other hand,it solves the problem that the MSER algorithm has high complexity and low accuracy when extracting the most stable extreme region.In this paper,the proposed algorithm is tested and evaluated on the ICDAR data set.The experimental results show that the method has superiority.
基金
This work is supported by State Grid Shandong Electric Power Company Science and Technology Project Funding under Grant Nos.520613180002,62061318C002
the Fundamental Research Funds for the Central Universities(Grant No.HIT.NSRIF.201714)
Weihai Science and Technology Development Program(2016DX GJMS15)
Key Research and Development Program in Shandong Provincial(2017GGX90103).
