Progress In Computer Vision And Image Analysis (Series in by Horst Bunke, Juan Jose Villanueva, Gemma Sanchez

By Horst Bunke, Juan Jose Villanueva, Gemma Sanchez

This e-book is a set of clinical papers released over the last 5 years, exhibiting a wide spectrum of tangible examine issues and methods used to resolve hard difficulties within the components of computing device imaginative and prescient and photograph research. The booklet will attract researchers, technicians and graduate scholars.

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Additional resources for Progress In Computer Vision And Image Analysis (Series in Machine Perception & Artifical Intelligence) (Series in Machine Perception and Artificial Intelligence)

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These rules assure that the topological changes required to reduce the over-segmentation be easily handled through this merging mechanism. Figure 2 illustrates the steps in the evolution of the ISS algorithm for a sample of rock. Figure 2a shows a 256 gray-scale microscopic image of a polished rock after applying the PDE based denoising filter for 10 iterations. This particular image presents sharp transitions between regions presenting homogeneous but different intensities. A convenient processing order can be established, in this case, by sorting pixels according to the difference between the maximum and minimum graylevels (morphological gradient) inside the pixel neighborhood N(p).

At first, implemented in the PDE-based level set framework [20, 21], an edge preserving smoothing algorithm removes noise by constraining the surface to evolve according to its vertically projected mean curvature [29, 27]. Secondly, inspired in the watershed transformation [26] and implemented in the Mathematical Morphology framework [3, 4, 16, 17, 25, 26, 2, 8, 9], a fast and robust algorithm An Interactive Algorithm for Image Smoothing and Segmentation 23 segments the image simulating an immersion on its surface.

The original 256 gray-scale image is depicted in (a). The simultaneous convergence problem can be observed in (b) using the bubbles method with bubbles initialized at image minima and in (c) using the front-propagation method with 36 seeds initialized by hand. Notice that while some bubbles are still evolving, some have converged and others are being merged. Another problem, “leaking” can occur through weak or diffuse edges, as can be observed in (d) and (e), with seeded region-growing method and CBMA [2] respectively.

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