An Efficient System for Hazy Scene Text Detection using a Deep CNN and Patch-NMS

Abstract

Scene text detection systems detect texts in natural scene images. Hazy scene text detection is a specific case of scene text detection where detection is done in hazy weather conditions. Haze affects the contrast of the image. In this paper, we reframe the traditional two class hazy scene text detection problem into a four class problem. We develop a deep learning based model that combines features from all layers for accurate and fast text detection from hazy images. In addition, we develop a novel training approach for the four class problem. Merging and patch-NMS are used as post processing steps for fast word detection. We also create a new dataset of hazy scene images and obtain significant improvements on an existing hazy scene text dataset.