HsiehYiChia
commented
6 years ago The text classification system consist of 2 classifiers. All the detected ERs will go through strong classifier, and classified as strong-text and non-strong-text. Non-strong-text candidates will then go through weak classifier, and classified as weak-text and non-text.
Strong text classifier has higher precision but lower recall, and vice versa. Recall and precision is a trade-off. The 2-stage classifier aim to provide better recall and precision than single classifier. You can refer to "Canny Text Detector: Fast and Robust Scene Text Localization Algorithm", which this algorithm is based on.
Your English is good enough to deliver your question, btw :D
Sincky
I know it uses the machine classifier to judge non-text. But i didn't know what does it mean to be “strong” and “weak”? What are the "strong" and "weak" classifying based on? I want to learn it and make it better to classify。
My English is no well，maybe you can't easily to read。 Hope to get your reply.
//Chinese 中文 strong和weak分类器是根据什么来判定的？ 我想去深入了解一下并把它改进改进。