Shape from texture and contour by weak isotropy
Artificial Intelligence
Shape from Texture Using Local Spectral Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computing Local Surface Orientation and Shape from Texture forCurved Surfaces
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Text Detection from Natural Scene Images: Towards a System for Visually Impaired Persons
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
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This paper presents a method for estimating the orientation of planar text surfaces using the edge-direction distribution (EDD) extracted from the image as input to a neural network. We consider canonical rotations and we developed a mathematical model to analyze how the EDD changes with the rotation angle under orthographic projection. In order to improve performance and solve quadrant ambiguities, we adopt an active-vision approach by considering a pair of images (instead of only one) with a slight rotation difference between them. We then use the difference between the two EDDs as input to the network. Starting with camera-captured front-parallel images with text, we apply single-axis synthetic rotations to verify the validity of the EDD transform model and to train and test the network. The presented text-pose estimation method is intended to provide navigation guidance to a mobile robot capable of reading the textual content encountered in its environment.