The scene text detection algorithm builds a component tree of an image by thresholding it step-by-step from 0 to 255. To enhance the results, this process is done for each color channel, intensity, and gradient magnitude images. After that, the connected components obtained from successive levels are hierarchically organized depending on their inclusion relationship as shown in the following diagram. This tree organization may contain a huge number of regions:

Tree organization example

Thus, the algorithm selects some regions following two stages. Firstly, area, perimeter, bounding box, and Euler number descriptors are computed for each region and used in order to estimate the class-condition probability. External regions with local maximum probabilities are selected if their values are above a global limit and the difference between their local maximum and minimum is also above a specified limit.

The second stage consists of classifying the external regions selected in...