neural - fuzzy logic for automatic object recognition
DESCRIPTION
NEURAL - FUZZY LOGIC FOR AUTOMATIC OBJECT RECOGNITION. INTRODUCTION. Artificial Neural Networks is a system modeled on the human brain. It is an attempt to simulate with specialized hardware or sophisticated software the multiple layers of simple processing elements called neurons. - PowerPoint PPT PresentationTRANSCRIPT
NEURAL - FUZZY LOGIC FOR AUTOMATIC OBJECT
RECOGNITION.
INTRODUCTION
• Artificial Neural Networks is a system modeled on the human brain. It is an attempt to simulate with specialized hardware or sophisticated software the multiple layers of simple processing elements called neurons.
• Fuzzy set theory resembles human reasoning in its use of approximate or corrupted data to generate decision.
• Integration of ANN and Fuzzy logic can provide a very efficient solution for Target recognition.
MODULES OF THE ATR SYSTEM
• Acquisition: Capturing data with a sensor.• Transformation: Preprocessing of the image.• Segmentation: Identifying regions of interest, using
Freeman code for border detection.• Geometric features: Usage of Hough Transform for
identifying hidden lines also.• Target Database: Tabulated values for each model.• Model Matching: Matching measured values with
tabulated values.
IMPLEMENTATION OF NEURAL - FUZZY LOGIC
• With the inclusion of fuzzy logic in the ATR system, even when one dimension is obscured a match can be made with the remaining two dimensions.
• Network is trained using a Back Propagation algorithm
BACK PROPAGATION ALGORITHM
OTHER APPLICATIONS
• Character Recognition
• Automatic Phonetic Recognition
• Facial Recognition
• Signature Recognition
• Fingerprint Recognition
CONCLUSION• The computing world has a lot to gain from
Neural Networks.• Their ability to learn makes them flexible and very
powerful.• The most exciting aspect of Neural Networks is
the possibility that some day ‘conscious’ networks may be produced.
• Neural Networks have a huge potential and we will get the best of them when integrated with computing, AI, Fuzzy logic and related subjects.
BIBLIOGRAPHY
BOOKS:
Digital Image Processing – Rafael C. Gonzalez / Richard E. Woods
Neural Networks – James A. Freeman / David M. Skapura
WEB SITES:
http://www.dacs.dtic.mil/techs/neural/neural.title.html
http://www.emsl.pnl.gov:2080/docs/cie/neural/neural.homepage.html
http://www.elsevier.nl/locate/patrec
http://www.mathworks.com/products/image/description
http://www.cse.msu.edu
PRESENTED BY
NAGINI INDUGULA (4/4 CSE) 98311A0515
Sree Nidhi Institute of Science and Technology Hyderabad
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