SYLLABUS 4 JNTU BME - IMAGE PROCESSING AND PATTERN RECOGNITION

IMAGE PROCESSING AND PATTERN RECOGNITION

UNIT-I
Basic Concepts, Pattern Recognition Systems, Fundamental Problems in pattern recognition system design, Design concepts and Methodologies – Character recognition – Speech recognition – Finger print Recognition – Pattern Recognition Model.

UNIT – II:
Decision Functions – Linear Decision functions – Distance functions. Minimum distance classification, clustering concepts, Cluster seeking algorithms, Maximum distance, K- means Algorithms.

UNTI – III:
Bayes classified decision function – For Baye’s classifier Baye’s Classifier for normal patterns. Trainable pattern classifiers – deterministic approach, perception approach reward – punishment concept.

UNIT – IV:
Gradient approach – Gradient Descent algorithms – LMSE Algorithms – Multi category classification.

UNIT – V:
Trainable pattern classifiers, statistical approach – stochastic approximation methods, Robbin Minro algorithms – increment correction algorithms, LMSE algorithms. Syntactic patter recognition – formulation – syntax directed recognition – picture descript.

UNIT – VI:
Digital Image fundamentals: Representation, elements – image transforms – Fast Fourier transform, DCT and DWT.

UNIT – VII:
Image enhancement- Spatial domain - frequency domain methods – Histogram, Modification techniques – Image Smoothing, image sharpening.

UNIT – VIII:
Image encoding - Fidelity criteria, Encoding process, Mapping – Quantizer coder – Image Segmentation – Masks – Point detection – Line Detection – Edge Detection.

TEXT BOOKS:
1. Digital Image Processing – by R.C. Gonzalez & R.E. Woods, Addison Wesley.
2. Pattern Recognition Principles – J.T.TOU.R.C. Gonzalez, Addison Wesley.
REFERENCE:
1. Fundamentals of Digital Image Processing – by A.K. Jain, PHI Pearson Education