By Sebastiano Battiato
This ebook constitutes the completely refereed court cases of the sixteenth overseas convention on complex strategies for clever imaginative and prescient platforms, ACIVS 2015, held Catania, Italy, in October 2015. The seventy six revised complete papers have been conscientiously chosen from 129 submissions.
Read or Download Advanced Concepts for Intelligent Vision Systems: 16th International Conference, ACIVS 2015, Catania, Italy, October 26-29, 2015. Proceedings PDF
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Extra info for Advanced Concepts for Intelligent Vision Systems: 16th International Conference, ACIVS 2015, Catania, Italy, October 26-29, 2015. Proceedings
Xn is deﬁned X So the X α-sparse. ,n xi 0 . V. Umnov et al. t. X 0,inf ≤ α. This problem can be solved using any sparse dictionary learning algorithm. In our work we use the K-SVD algorithm  for dictionary learning and OMP algorithm  for sparse coding. 3 Ringing Suppression Method The proposed method requires a set of images for learning. We split all images into overlapping 6 × 6 blocks and process each block separately. The images from the learning set are used to create a set of corresponding original blocks and blocks with ringing eﬀect.
Authors of  propose a new descriptor called RSD-HoG. It is based on the RSD-DOG 25 orientation of the edges. The edge orientations are extracted by using a rotating half Gaussian kernel. The descriptor is constructed in a novel way, by embedding the response of the rotating half Gaussian kernel in a Histogram of oriented Gradient (HoG) framework. e. how much the curve bends at that point. The authors of  use an oriented second derivative ﬁlter of Gaussians to capture isotropic as well as anisotropic characteristics of surface by the use of single scale for descriptor generation.
The visual results show that the estimated blur is ﬁtted with human blur perception. The quantitative evaluation is made comparing bl index with OCR accuracy. We calculated SROCC for 25 sets of the database DIQA with the estimated blur. This experiment shows that our blur estimation method can rank and select images with best OCR accuracy. In addition, the measured Pearson’s correlation scores for 25 sets show that our method outperforms unsupervised and supervised approaches. Next step is to use the present computation in order to improve the quality of the document and in particular the OCR accuracy.