By Sebastiano Battiato
This publication constitutes the completely refereed complaints 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 rigorously chosen from 129 submissions.
Read Online 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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This publication constitutes the refereed complaints of the eleventh overseas Joint convention on E-Business and Telecommunications, ICETE 2014, held in Vienna, Austria, in August 2014. ICETE is a joint overseas convention integrating 4 significant parts of information which are divided into six corresponding meetings: overseas convention on information conversation Networking, DCNET; foreign convention on E-Business, ICE-B; overseas convention on Optical conversation structures, OPTICS; foreign convention on safeguard and Cryptography, SECRYPT; foreign convention on instant details structures, WINSYS; and overseas convention on sign Processing and Multimedia, SIGMAP.
Additional resources for Advanced Concepts for Intelligent Vision Systems: 16th International Conference, ACIVS 2015, Catania, Italy, October 26-29, 2015. Proceedings
In [2,4] authors propose methods of multi-scale edge detection, where the scale of detection for each edge can roughly approximate blur level. In  neural networks are used. In  edge neighborhood is expanded in radial-symmetric functions with the method of principal components as a classiﬁer of blur level. In this work we present a novel approach for edge width estimation suggested in  which is accurate and is robust to noise. Then we demonstrate the eﬀectiveness of the proposed method for the problem of obtaining the defocus map from a single image.
2 Estimating the Direction of Second Order Statistics Such as Ridges and Valleys By convolving the image patch with the DHSF (by the technique of rotating the images, as explained above), for each pixel in the image patch we obtain a pixel signal which captures a directional second order information around the pixel. The idea is to extract the directions at which these second order statistics such as ridges and valleys occur and to construct a descriptor from this information. Let us consider D(x, y, θ) to be the pixel signal obtained at pixel P located at (x, y).
Here, we test the descriptors using similarity threshold based matching, since this technique is better suited for representing the distribution of the descriptor in its feature space. Due to the space limitation, we restrain from going into the details of this method. A detailed description of this method can be found in . The results are presented using the recall vs 1-precision curves. 4, recall is deﬁned as the total number of correctly matched aﬃne regions over the number of corresponding aﬃne regions between two images of the same scene.