Hull Number Detection for Ship Images Based on Image Super-Resolution

At present, natural scene text detection methods based on deep learning have achieved outstanding results in many applications. Hull number belongs to the text object, detecting the hull number successfully plays an important role in maritime military and shipping. However, the hull number occupies a relatively small area in the ship image as well as it could be blurred or deformed due to the reason of the photo environment, which made the accuracy of detecting the hull number directly on ship images has great room for improvement. Therefore, this article proposes a hull number detection method based on image super-resolution(SR), which first performs SR on a single ship image, then implements hull number detection on the SR ship image. To reduce the time consumption of the SR process, the original image is divided into multiple grids that perform SR in parallel. Finally, these multiple SR grids are synthesized into a new SR image. Experiments proved that the detection accuracy of the hull number is significantly improved on SR ship images.