盲文
计算机科学
性格(数学)
特征(语言学)
自然(考古学)
计算机视觉
字符识别
人工智能
GSM演进的增强数据速率
集合(抽象数据类型)
视力受损
语音识别
模式识别(心理学)
图像(数学)
人机交互
数学
哲学
考古
程序设计语言
操作系统
历史
语言学
几何学
作者
Liqiong Lu,Dong Wu,Jianfang Xiong,Liang Zhou,Faliang Huang
摘要
Braille character detection helps communication between normal and visually impaired people. The existing Braille detection methods are all aimed at scanning Braille document images while ignoring natural scene Braille images and CNN shining in the field of pattern recognition is rarely used for Braille detection. Firstly, a natural scene Braille image data set named NSBD was constructed. Then, an anchor-free Braille character detection based on the edge feature was proposed by analyzing that Braille characters in natural scene images that are relatively small in size, and a Braille character is composed of Braille dots that werelocated at the edge region of Braille character. Finally, the performance of the proposed method and other classic methods based on CNN was compared on NSBD. The experimental results show that the proposed method has good performance.
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