{ "cells": [ { "cell_type": "markdown", "metadata": { "collapsed": false }, "source": [ "This notebook is from: http://scikit-image.org/docs/dev/auto_examples/plot_gabor.html\n", "\n", "Your assignment is simply to run it, sign your name, and send it to the TA" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "YOUR NAME:" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
In this example, we will see how to classify textures based on Gabor filter\n", "banks. Frequency and orientation representations of the Gabor filter are similar\n", "to those of the human visual system.
\n", "The images are filtered using the real parts of various different Gabor filter\n", "kernels. The mean and variance of the filtered images are then used as features\n", "for classification, which is based on the least squared error for simplicity.
\n", "