Introduction to Pattern Recognition

Introduction to Pattern Recognition

•          Machine Perception

•           An Example

•           Pattern Recognition Systems

•           The Design Cycle

•           Learning and Adaptation

Machine Perception

•          Build a machine that can recognize patterns:

•          Speech recognition

•          Fingerprint identification

•          OCR (Optical Character Recognition)

•          DNA sequence identification

An Example

•          “Sorting incoming Fish on a conveyor according to species using optical sensing”

                                                               

 

Problem Analysis

•          Set up a camera and take some sample images to extract features

•          Length

•          Lightness

•          Width

•          Number and shape of fins

•          Position of the mouth, etc…

•          This is the set of all suggested features to explore for use in our classifier!

•          Preprocessing

•          Use a segmentation operation to isolate fishes from one another and from the background

•          Information from a single fish is sent to a feature extractor whose purpose is to reduce the data by measuring certain features

•          The features are passed to a classifier