Image Segmentation Using Hardware Forest Classifiers.
Richard Neil PittmanAlessandro ForinAntonio CriminisiJamie ShottonAtabak MahramPublished in: FCCM (2013)
Keyphrases
- image segmentation
- training data
- low cost
- real time
- supervised classification
- graph cuts
- image processing
- method for image segmentation
- decision trees
- boundary detection
- linear classifiers
- multiscale
- hardware and software
- classification systems
- markov random field
- machine learning algorithms
- class labels
- feature set
- support vector
- feature selection
- computing systems
- level set method
- computer vision
- massively parallel
- classification algorithm
- segmentation method
- energy function
- training set
- image segmentation algorithm
- training examples
- gray level
- naive bayes
- segmentation algorithm
- contour detection
- computer systems
- ensemble classifier
- texture segmentation
- machine learning
- learning algorithm
- level set
- neural network
- classification rate
- embedded systems
- region growing
- deformable models
- svm classifier
- training samples
- active contours
- hardware implementation
- machine learning methods
- image analysis
- multiple classifiers
- hardware architecture
- probabilistic relaxation