Download Advanced Concepts for Intelligent Vision Systems: 16th by Sebastiano Battiato PDF

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By Sebastiano Battiato

This publication constitutes the completely refereed lawsuits of the sixteenth foreign convention on complex innovations 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.

Acivs 2015 is a convention targeting ideas for development adaptive, clever, secure and safe imaging platforms. the focal point of the convention is on following subject: low-level picture processing, video processing and digicam networks, movement and monitoring, protection, forensics and biometrics, intensity and 3D, picture caliber development and evaluation, category and popularity, multidimensional sign processing, multimedia compression, retrieval, and navigation.

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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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Additional info for Advanced Concepts for Intelligent Vision Systems: 16th International Conference, ACIVS 2015, Catania, Italy, October 26-29, 2015. Proceedings

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Umnov et al. The proposed method is based on the joint sparse coding method, which was previously used for image deblurring and image super-resolution [25]. 2. Fig. 1. Example of the ringing effect: reference image (left) and image with ringing effect (right). 1 Ringing Suppression Problem Formulation Consider the ringing effect produced by high frequency cut-off filter Rd which removes all the frequencies in the Fourier domain outside the circular mask with 1 centered at zero frequency point: radius ωd = 2d Rd (I) = F −1 (F(I) · ld ), where F and F −1 are Fourier transform and inverse Fourier transform respectively, ld is the mask ⎧ ⎨ 1, if ωx2 + ωy2 ≤ ωd , ld (ωx , ωy ) = ⎩ 0, if ωx2 + ωy2 > ωd .

International Journal of Computer Vision (IJCV) 60, 63–86 (2004) 5. : Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. PAMI 24, 971–987 (2002) 6. : Description of interest regions with local binary patterns. Pattern Recognition 42, 425–436 (2009) 7. : Image region description using orthogonal combination of local binary patterns enhanced with color information. Pattern Recognition 46, 1949–1963 (2013) 8. : PCA-SIFT: a more distinctive representation for local image descriptors.

Also, for non-isolated edge profiles we isolate the central edge: we find the nearest local maximum to the right from the center and the nearest local minimum to the left, and duplicate those values (see Fig. 2). Fig. 2. Edge profile examples and the result of the proposed edge width estimation method. The blue thin line is the original profile, the red thick line is an isolated edge, the green puncture line is a model edge with found edge width. 2 Full Defocus Map Using sparse defocus map at edge locations, the full defocus map is recovered by an edge-aware interpolation method [8].

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