Pattern Recognition Using Artificial Neural Networks

Ace ofHearts

Eyal Ittah (60407301)Ittai Doron (53084489)

IntroductionIntroduction

Classify images of playing cards by their Classify images of playing cards by their suit and value suit and value

Pattern RecognitionPattern Recognition

Sensor – existing imagesSensor – existing images

Feature extraction mechanism – Feature extraction mechanism – Relaxation Labeling on color imagesRelaxation Labeling on color images

Classification scheme –Classification scheme –Artificial Neural Network used to classify Artificial Neural Network used to classify suit and valuesuit and value

Relaxation LabelingRelaxation Labeling

Objects – pixelsObjects – pixels

Labels – object, backgroundLabels – object, background

Initial confidence – degree of whiteInitial confidence – degree of white

Artificial Neural NetworksArtificial Neural Networks Neurons as basic Neurons as basic calculation unitscalculation units

Input layer - Each Input layer - Each neuron a single input neuron a single input variable variable

Hidden layers Hidden layers

Output layer - Each Output layer - Each neuron represents a neuron represents a single output variable.single output variable.

Artificial Neural NetworksArtificial Neural Networks

Training the networkTraining the network Supervised learningSupervised learning Back-propagationBack-propagation Learning rateLearning rate

Card classificationCard classification

Card classification (noisy Card classification (noisy image)image)

ConclusionsConclusions

Using two ANNs instead of one Using two ANNs instead of one

Decreasing the learning rate of the ANN Decreasing the learning rate of the ANN

Using an output neuron for each classUsing an output neuron for each class