Graphics Multimedia

Bezier & Splines in Image Processing & Machine Vision by Sambhunath Biswas

By Sambhunath Biswas

This e-book offers with numerous photograph processing and computer imaginative and prescient difficulties successfully with splines and contains: the importance of Bernstein Polynomial in splines, designated insurance of Beta-splines purposes that are quite new, Splines in movement monitoring, quite a few deformative types and their makes use of. ultimately the e-book covers wavelet splines that are effective and potent in numerous picture applications.

Show description

Read or Download Bezier & Splines in Image Processing & Machine Vision PDF

Best graphics & multimedia books

Dynamical systems and fractals: computer graphics experiments in Pascal

This learn of chaos, fractals and complicated dynamics is meant for somebody acquainted with pcs. whereas conserving the math to an easy point with few formulation, the reader is brought to a space of present medical examine that was once scarcely attainable till the provision of pcs. The booklet is split into major components; the 1st offers the main attention-grabbing difficulties, each one with an answer in a working laptop or computer application structure.

Computer graphics in geology: three-dimensional computer graphics in modeling geologic structures and simulating geologic processes

Point of view perspectives, corresponding to block diagrams and fence diagrams have constantly been an immense technique of medical visualiza- tion in geology. complicated 3-dimensional desktop gra- phics is a brand new software for the development of such perspectives. The booklet includes papers provided on the first huge interna- tional assembly (Freiburg, October 8-11, 1990) that introduced jointly operating teams engaged in improvement of three-D visua- lization courses for geologic reasons, and integrated humans fromuniversities, govt businesses, the mining undefined (especially oil businesses) and from software program businesses enga- ged in geology and geographic info structures.

Forensic GIS: The Role of Geospatial Technologies for Investigating Crime and Providing Evidence

Quite a few disciplines and professions have embraced geospatial applied sciences for accumulating, storing, manipulating, examining and exhibiting spatial facts to enquire crime, prosecute and convict offenders, exonerate suspects and post proof in civil proceedings. The purposes, acceptability and relevance and procedural legality of every geospatial applied sciences differ.

Riemannian Computing in Computer Vision

This ebook provides a accomplished treatise on Riemannian geometric computations and similar statistical inferences in numerous desktop imaginative and prescient difficulties. This edited quantity contains bankruptcy contributions from major figures within the box of desktop imaginative and prescient who're utilizing Riemannian geometric methods in difficulties equivalent to face acceptance, job attractiveness, item detection, biomedical snapshot research, and structure-from-motion.

Additional info for Bezier & Splines in Image Processing & Machine Vision

Example text

A schematic description of variable order local surface approximation is given below. Algorithm local approx (input image, th, a , q, p) begin step 1: find the most dispersed region, Ωk in the input image; find the residual error surface for it with respect to order q; step 2: find p using the Algorithm global approx (Ωk , th, a , p); step 3: if p ≥ q, a pre-assigned positive integer then goto step 4 else assign an index for the region and return p; step 4: stop; end; To summarize, this scheme is a two stage process.

In the present context, it can be used to examine the graylevel similarity between the segmented region/patches and the original image. Consider the segmented image where all patches under respective thresholds are replaced by their average value. The correlation between the segmented and input images provides an idea about how a segmented patch is nearer to the corresponding region in the original input image. For a good segmentation, the correlation coefficient between the two images should be very high.

This should be merged to the neighboring region having the closest gray value in the 3 × 3 neighborhood of the single pixel region. 5 Evaluation of Segmentation Evaluation of segmentation is very important, though adequate attention is not always paid. For evaluation of segmentation, one can consider region homogeneity and contrast along the boundary points. 5 Evaluation of Segmentation 49 inter-region boundaries. Merging should have very little effect on the overall contrast of the image. The following objective measures for quantitative evaluation of segmentation are helpful.

Download PDF sample

Rated 4.91 of 5 – based on 34 votes