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 conte...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.展开更多
This paper proposes a new approach to the water flow algorithm for text line segmentation. In the basic method the hypothetical water flows under few specified angles which have been defined by water flow angle as par...This paper proposes a new approach to the water flow algorithm for text line segmentation. In the basic method the hypothetical water flows under few specified angles which have been defined by water flow angle as parameter. It is applied to the document image frame from left to right and vice versa. As a result, the unwetted and wetted areas are established. These areas separate text from non-text elements in each text line, respectively. Hence, they represent the control areas that are of major importance for text line segmentation. Primarily, an extended approach means extraction of the connected-components by bounding boxes over text. By this way, each connected component is mutually separated. Hence, the water flow angle, which defines the unwetted areas, is determined adaptively. By choosing appropriate water flow angle, the unwetted areas are lengthening which leads to the better text line segmentation. Results of this approach are encouraging due to the text line segmentation improvement which is the most challenging step in document image processing.展开更多
基金This work is supported by State Grid Shandong Electric Power Company Science and Technology Project Funding under Grant Nos.520613180002,62061318C002the Fundamental Research Funds for the Central Universities(Grant No.HIT.NSRIF.201714)+1 种基金Weihai Science and Technology Development Program(2016DX GJMS15)Key Research and Development Program in Shandong Provincial(2017GGX90103).
文摘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.
文摘This paper proposes a new approach to the water flow algorithm for text line segmentation. In the basic method the hypothetical water flows under few specified angles which have been defined by water flow angle as parameter. It is applied to the document image frame from left to right and vice versa. As a result, the unwetted and wetted areas are established. These areas separate text from non-text elements in each text line, respectively. Hence, they represent the control areas that are of major importance for text line segmentation. Primarily, an extended approach means extraction of the connected-components by bounding boxes over text. By this way, each connected component is mutually separated. Hence, the water flow angle, which defines the unwetted areas, is determined adaptively. By choosing appropriate water flow angle, the unwetted areas are lengthening which leads to the better text line segmentation. Results of this approach are encouraging due to the text line segmentation improvement which is the most challenging step in document image processing.
