Automatic signboard region detection is the first step of information extraction about establishments from an image, especially when there is a complex background and multiple signboard regions are present in the image. Automatic signboard detection in Bangladesh is a challenging task because of low quality street view image, presence of overlapping objects and presence of signboard like objects which are not actually signboards. In this research, we provide a novel dataset from the perspective of Bangladesh city streets with an aim of signboard detection, namely Bangladesh Street View Signboard Objects (BSVSO) image dataset. We introduce a novel approach to detect signboard accurately by applying smart image processing techniques and statistically determined hyperparameter based deep learning method, Faster R-CNN. Comparison of different variations of this segmentation based learning method have also been performed in this research.
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