Computer Analysis of Visual Textures by Fumiaki Tomita, Saburo Tsuji

By Fumiaki Tomita, Saburo Tsuji

This e-book offers theories and methods for notion of textures by way of machine. Texture is a homogeneous visible development that we understand in surfaces of gadgets reminiscent of textiles, tree barks or stones. Texture research is among the first very important steps in machine imaginative and prescient on the grounds that texture offers very important cues to acknowledge real-world gadgets. an enormous a part of the e-book is dedicated to two-dimensional research of texture styles by way of extracting statistical and structural positive factors. It additionally bargains with the shape-from-texture challenge which addresses restoration of the third-dimensional floor shapes in accordance with the geometry of projection of the skin texture to the picture airplane. belief continues to be mostly mysterious. understanding a working laptop or computer imaginative and prescient approach which may paintings within the actual international calls for extra examine and ex­ periment. potential of textural notion is a key part. we are hoping this publication will give a contribution to the development of desktop imaginative and prescient towards powerful, worthy structures. vVe want to show our appreciation to Professor Takeo Kanade at Carnegie Mellon college for his encouragement and assist in scripting this e-book; to the individuals of machine imaginative and prescient part at Electrotechni­ cal Laboratory for delivering a great learn atmosphere; and to Carl W. Harris at Kluwer educational Publishers for his assist in getting ready the manuscript.

Show description

Read or Download Computer Analysis of Visual Textures PDF

Best computer vision & pattern recognition books

Biometrics: Personal Identification in Networked Society

Biometrics: own identity in Networked Society is a finished and available resource of state of the art info on all present and rising biometrics: the technology of immediately picking contributors in response to their physiological or habit features. specifically, the booklet covers: *General ideas and concepts of designing biometric-based structures and their underlying tradeoffs *Identification of vital matters within the evaluate of biometrics-based structures *Integration of biometric cues, and the combination of biometrics with different current applied sciences *Assessment of the features and boundaries of other biometrics *The finished exam of biometric equipment in advertisement use and in examine improvement *Exploration of a few of the varied privateness and defense implications of biometrics.

Information-Theoretic Evaluation for Computational Biomedical Ontologies

The advance of powerful tools for the prediction of ontological annotations is a crucial objective in computational biology, but comparing their functionality is hard as a result of difficulties as a result of the constitution of biomedical ontologies and incomplete annotations of genes. This paintings proposes an information-theoretic framework to judge the functionality of computational protein functionality prediction.

A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability)

A self-contained and coherent account of probabilistic options, protecting: distance measures, kernel principles, nearest neighbour principles, Vapnik-Chervonenkis thought, parametric class, and have extraction. every one bankruptcy concludes with difficulties and workouts to extra the readers knowing.

Additional resources for Computer Analysis of Visual Textures

Sample text

The following structural texture properties are extracted from the second-order statistics of edge directions. J. •. H I ,,1' ··- I • 1 ,~ • • I. - I! :· I • I I s' ,• r I s •t. I .. · I I • I •J • I I l' ·r·I . 'I . -..... , ' 1 ll :j . 1 't i 1·'·i·t. t. s i •/r' I : "a ~ • '• ~ ~· J' • f : • , • I,! I ·I·I ...... I I ,,_, • .. ,.. I - ' ).. , . _: J""'i ,. , . . -·s - _ . . -:-- •• i , . I - . r . . ttl, I. "', -·'I ~ ,,-. _ • ) , • 1: t:. •t .. - " I , ........ , . :r: . -:- '( . ,: r .

0 >> ' ·• . ' .... ,. ' + •• • ::. • ·: . . . ::: .... ,. . . • . • •••• A>>> . : . ~ > > 0 A wo ·~ ,. • . ~· .......... ·~: ... . '... . ..... . ~ ~·-- A A 0 0 0 0- ~· >, '' ' • > ... 8: (a) Image containing two regions (triangle and background) of different average intensity (probabilities of black points are 0. 3, respectively); (b) Result of applying the fixed-size neighborhood method; (c) Result of applying the variable-size neighborhood method.

L. L. L L. L. L. L. L. L. L. L.. L. L. L. L. L. L. L L.. L. 1... L. L. L L. L. L L.. L.. L.. L.. L L.. L 1... L L.. L.. 1... 1... 1... L.. 1... J,JL.. L L 1... L L. L. L.. L. L.. L L L. ,l. 1... JJ L. L.. L. _. JL.. L. 1... L 1... JL L.. L L. L. L L. L. 1... l... L. L. L.. L.. L. 13: (a) Textures with different orientation of lines; (b) Textures with the same length and orientation of lines (from Shatz, 1977). 5. Spatial Density: spatial density of place-tokens defined in the different possible ways, measured using a small selection of neighborhood sizes.

Download PDF sample

Rated 4.54 of 5 – based on 23 votes

Categories: Computer Vision Pattern Recognition