Sciweavers

Free Online Productivity Tools i2Speak i2Symbol i2OCR iTex2Img iWeb2Print iWeb2Shot i2Type iPdf2Split iPdf2Merge i2Bopomofo i2Arabic i2Style i2Image i2PDF iLatex2Rtf Sci2ools

7

ACCV
1998
Springer

favoriteEmaildiscussreport

113views Computer Vision» more ACCV 1998»

Optimising the Complete Image Feature Extraction Chain

13 years 9 months ago

Optimising the Complete Image Feature Extraction Chain

Download www.cs.bris.ac.uk

The hypothesis veri cation stage of the traditional image processing approach, consisting of low, medium, and high level processing, will su er if the set of low level features extracted are of poor quality. We investigate the optimisation of the feature extraction chain by using Genetic Algorithms. The tness function is a performance measure which re ects the quality of an extracted set of features. We will present some results and compare them with a Hill-Climbing approach.

Majid Mirmehdi, Phil L. Palmer, Josef Kittler

Real-time Traffic

ACCV 1998 | Computer Vision | Hypothesis Veri Cation | Image Processing Approach | Low Level Features |

claim paper

Related Content

» Proper Names Extraction from Fax Images Combining Textual and Image Features

» A Set of Chain Code Based Features for Writer Recognition

» Representative feature chain for single gallery image face recognition

» Feature Extraction of Scale Pattern in Animal Textile Fibers

» Automatic Registration of Range Images Based on Correspondence of Complete Plane Patches

» ContentBased Image Retrieval of Skin Lesions by Evolutionary Feature Synthesis

» Face Identification by SIFTbased Complete Graph Topology

» 2D Ultrasound Probe Complete Guidance by Visual Servoing Using Image Moments

» Face Boundary Extraction

Post Info
More Details (n/a)

Added	05 Aug 2010
Updated	05 Aug 2010
Type	Conference
Year	1998
Where	ACCV
Authors	Majid Mirmehdi, Phil L. Palmer, Josef Kittler

Comments (0)