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NEURAL - FUZZY LOGIC FOR AUTOMATIC OBJECT RECOGNITION

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.

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NEURAL - FUZZY LOGIC FOR AUTOMATIC OBJECT RECOGNITION

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  1. NEURAL - FUZZY LOGIC FOR AUTOMATIC OBJECT RECOGNITION .

  2. 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.

  3. 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.

  4. 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

  5. BACK PROPAGATION ALGORITHM

  6. OTHER APPLICATIONS • Character Recognition • Automatic Phonetic Recognition • Facial Recognition • Signature Recognition • Fingerprint Recognition

  7. 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.

  8. BIBLIOGRAPHY

  9. PRESENTED BY • NAGINI INDUGULA (4/4 CSE) 98311A0515 Sree Nidhi Institute of Science and Technology Hyderabad

  10. ?? QUESTIONS ??

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