The invention discloses an end-to-end identification method for a scene text with a random shape. The method comprises the steps of extracting a text characteristic through a characteristic
pyramid network for generating a candidate
text box by an area extracting network; adjusting the position of the candidate
text box through quick area classification regression
branch for obtaining more accurate position of a text bounding box; inputting the position information of the bounding box into a dividing
branch, obtaining a predicated character sequence through a pixel voting
algorithm; and finally
processing the predicated character sequence through a weighted editing distance
algorithm, finding out a most matched word of the predicated character sequence in a given dictionary, thereby obtaining a final text identification result. According to the method of the invention, the scene texts with the random shape can be simultaneously detected and identified, wherein the scene texts comprisehorizontal text, multidirectional text and curved text. Furthermore end-to-end training can be completely performed. Compared with prior art, the identification method according to the invention has advantages of obtaining advantageous effects in accuracy and versatility, and realizing high application value.