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Multi-directional Text Detection Method in Natural Scenes

A text detection and natural scene technology, applied in the field of computer vision, can solve the problems of poor performance outside the training set, strong dependence on the training set, etc., and achieve the effect of suppressing false boundaries and strong adaptability

Active Publication Date: 2018-02-13
SOUTHEAST UNIV
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AI Technical Summary

Problems solved by technology

Rule-based methods are more sensitive to combined text or region breaks, while learning-based methods are highly dependent on the training set and perform poorly outside the training set

Method used

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  • Multi-directional Text Detection Method in Natural Scenes

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Embodiment Construction

[0045] Principle of the present invention is specifically described below in conjunction with accompanying drawing:

[0046] 1. Boundary enhancement MSER region extraction

[0047] The original MSER algorithm uses the region where the area of ​​the extremum region changes to a minimum value as the largest stable extremum region. However, the image boundary is generally blurred, resulting in multiple nested stable extremum regions near the image boundary. The Canny edge detection operator adopts the non-maximum value suppression technology, which effectively suppresses the false boundary, and superimposes the generated boundary into the region. It can be found that the Canny boundary can assist in selecting the best region, thereby eliminating the "false" stable region Such as figure 2 (a) shown.

[0048] Boundary lifting MSER algorithm, recursively pair two regions with father-only child relationship and area change ΔS not exceeding 50% on the stable extremum region compone...

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Abstract

The present invention provides a multi-directional text detection method in a natural scene, and the specific steps are as follows: step 1, boundary promotion MSER region extraction; recursive pairs on the stable extremum region component tree obtained by the original MSER algorithm have a father-only child relationship and the area change ΔS is not For the two areas that exceed the first threshold, according to the boundary matching degree formula, the area with a small boundary matching degree is eliminated; Step 2, character sorting tree area sorting; Step 3, multi-layer fusion of characters to form a text line; Step 2 finally obtains the sorted character region set for multi-layer fusion, which is sequentially expanded fusion layer, free growth layer, bijective growth layer, and competition layer, and finally generates a text line.

Description

technical field [0001] The invention relates to pattern recognition, image processing, and artificial intelligence related technologies, and belongs to the field of computer vision. Background technique [0002] Text detection in natural scenes is interfered by many factors such as language, scale, font, illumination, contrast, viewing angle, direction, background, incomplete, blurred, broken, etc., and the detection accuracy cannot reach a high level. Text detection in natural scenes has not been well solved until now. The current research is mainly aimed at the detection of English text in the horizontal direction. The detection technology of multi-directional mixed languages ​​is relatively lagging behind. Many detection methods use the character in the horizontal direction as a priori knowledge, so the text detection effect in multiple directions is not ideal (such as [1], [2], [5]), and some detection methods limit the language to English characters, and the trained par...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/62G06K9/66
CPCG06V30/40G06V30/194G06F18/24
Inventor 杨彬夏思宇
Owner SOUTHEAST UNIV
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