New PDF release: Image Processing and Communications Challenges 7

By Ryszard S. Choraś

ISBN-10: 2552672752

ISBN-13: 9782552672751

ISBN-10: 3319238132

ISBN-13: 9783319238135

ISBN-10: 3319238140

ISBN-13: 9783319238142

This publication includes papers authorised for IP&C 2015, the foreign convention on photo Processing and Communications, held at UTP collage of technology and know-how, Bydgoszcz, Poland, September Sept. 11, 2015. This convention used to be the 8th version within the IP&C sequence of annual meetings. This ebook and the convention have the purpose to compile researchers and scientists within the extensive fields of snapshot processing and communications, addressing contemporary advances in concept, technique and purposes. The ebook could be of curiosity to a wide team of researchers, engineers and practitioners in photo processing and communications.

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Texture can be characterized by the statistical distribution of the image intensity using Grey Level Co-occurrence Matrix (GLCM), proposed by Haralick [6]. The co-occurrence matrix C(i, j) counts the co-occurrence of pixels with gray values i and j at a given distance d. The distance d is defined in polar coordinates (d, α), with discrete length and orientation. In practice, α takes the values 0◦ ; 45◦ ; 90◦ ; 135◦ . The co-occurrence matrix C(i, j) can now be defined as follows: C(i, j) = Pr (P( p1 ) = i ∧ P( p2 ) = j | | p1 − p2 | = d) (2) where Pr is probability, and p1 and p2 are positions in the gray-scale image P.

Springer, Berlin Heidelberg (2002) 5. : Scale & affine invariant interest point detectors. Int. J. Comput. Vision 60(1), 63–86 (2004) 6. : Evaluation of local detectors and descriptors for fast feature matching. Pattern Recognition (ICPR), 2012 21st (2012) 7. : Obstacle avoidance and navigation in the real world by a seeing robot rover. Technical Report CMU-RI-TR-3, Carnegie-Melon University, Robotics Institute (Sept. 1980) 8. : On a modification to the harris corner detector. In: proceedings of Symposium Svenska Sallskapet for Bildanalys, Stockholm.

2h and 3e). b3 = bmax ⊕ se (6) The final binary image of brain b is still defined as the largest connected component in image b3 . The size of the structuring element was determined empirically (for slices of the resolution 512 × 512 pixels and slice thickness equal to pixel spacing).

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Image Processing and Communications Challenges 7 by Ryszard S. Choraś


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