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Recognizing Text-Based Traffic Signs
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DOI：10.1109/TITS.2014.2363167.png)
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摘要
En 中文
We propose a novel system for the automatic detection and recognition of text in traffic signs. Scene structure is used to define search regions within the image, in which traffic sign candidates are then found. Maximally stable extremal regions (MSERs) and hue, saturation, and value color thresholding are used to locate a large number of candidates, which are then reduced by applying constraints based on temporal and structural information. A recognition stage interprets the text contained within detected candidate regions. Individual text characters are detected as MSERs and are grouped into lines, before being interpreted using optical character recognition (OCR). Recognition accuracy is vastly improved through the temporal fusion of text results across consecutive frames. The method is comparatively evaluated and achieves an overall F-measure of 0.87.
Keyword:
Maximally stable extremal region (MSER)
scene structure
text detection
traffic text sign recognition
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8.4
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被引数:
6.3W
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引用论文
Text String Detection From Natural Scenes by Structure-Based Partition and Grouping通过基于结构的划分和分组从自然场景中检测文本字符串
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OAAI分享收藏Complete Vision-Based Traffic Sign Recognition Supported by an I2V Communication SystemI2V通信系统支持的完整的基于视觉的交通标志识别.png)
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