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February 7, 2015 11:10
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| { | |
| "metadata": { | |
| "name": "", | |
| "signature": "sha256:9d0ccc107f797c5860c131b37983c0262a0f6992137d603b5c9db247e0b34016" | |
| }, | |
| "nbformat": 3, | |
| "nbformat_minor": 0, | |
| "worksheets": [ | |
| { | |
| "cells": [ | |
| { | |
| "cell_type": "heading", | |
| "level": 1, | |
| "metadata": {}, | |
| "source": [ | |
| "Efficient Graph-Based Image Segmentation." | |
| ] | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 4, | |
| "metadata": {}, | |
| "source": [ | |
| "By Abhijeet Kislay (GitHub ID: <a href='https://github.com/kislayabhi'>kislayabhi</a>)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "Here we are trying to address the problem of segmentating an image into regions." | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "Let $G=(V,E)$ be an undirected graph with vertices $v_i \\in V$.\n", | |
| "\n", | |
| "* Here in Image Segmentation, the elements in $V$ are pixels. \n", | |
| "* The weight of an edge is a measure of dissimilarity between two pixels connected by that edge.\n", | |
| "\n", | |
| "**Analogy**: The edges between two vertices in the same component should have relatively low weights, and edges between vertices in different components should have higher weights." | |
| ] | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 3, | |
| "metadata": {}, | |
| "source": [ | |
| "Pairwise Region Comparison Predicate" | |
| ] | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 4, | |
| "metadata": {}, | |
| "source": [ | |
| "Internal Difference" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "Internal difference of a component $\\mathbf{C}$ (a group of pixels) is the largest weight in the minimum spanning tree of the present group of pixels $\\mathbf{C}$. That is,\n", | |
| "\n", | |
| "$$Int\\mathbf{(C)}=\\max_{e\\in MST(C,E)} \\mathbf{w(e)}$$" | |
| ] | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 4, | |
| "metadata": {}, | |
| "source": [ | |
| "Difference Between" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "We define the difference between the two components $C_1, C_2$ to be the minimum weight edge connecting the two components.\n", | |
| "\n", | |
| "$$Dif(C_1,C_2)= \\min_{v_i\\in C_1, v_j\\in C_2,(v_i, v_j)} w(v_i, v_j)$$" | |
| ] | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 4, | |
| "metadata": {}, | |
| "source": [ | |
| "Threshold Function" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "A threshold function is used to control the degree to which the difference between components must be larger than minimum internal difference for locating a boundary in between them.\n", | |
| "\n", | |
| "$$\\mathbf{\\tau(C_1)}$$\n", | |
| "\n", | |
| "It is seen that for small components, $Int(C)$ is not a good estimate of the local characterstics of the data, and this happens to be one of the reason for using Threshold Function. \n", | |
| "\n", | |
| "Say in the extreme conditions where we are left only with a single pixel, the value of $\\mathbf{|C|}$ gets equal to 1. Here the value of $Int(C)=0$. Therefore, we use a threshold function based on the size of the component,\n", | |
| "\n", | |
| "$$\\tau(C)=k/|C|$$" | |
| ] | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 4, | |
| "metadata": {}, | |
| "source": [ | |
| "Minimum Internal Difference" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "$$MInt(C_1, C_2)=\\min(Int(C_1)+\\tau(C_1), Int(C_2)+\\tau(C_2))$$" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "The pairwise comparison predicate is defined here as:\n", | |
| "\n", | |
| "$$D(C_1, C_2)=true$$ $$if$$ $$ Dif(C_1, C_2)> M Int(C_1, C_2)$$\n", | |
| "\n", | |
| "Our aim here is to find if the difference between the components is large relative to the internal difference within at least one of the components( the one which is minumum)." | |
| ] | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 3, | |
| "metadata": {}, | |
| "source": [ | |
| "The Algorithm and Its Properties" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "The input is a graph $\\mathbf{G}=\\mathbf{(V,E)}$ with $\\mathbf{n}$ vertices and $\\mathbf{m}$ edges. The output is a segmentation of $\\mathbf{V}$ into components $\\mathbf{S=(C_1,...,C_r)}$.\n", | |
| "\n", | |
| "Our algorithm is very much alike the Kruksal's method of finding the MST.\n", | |
| "\n", | |
| "1. Sort E into \u03c0 = (o 1 , . . . , o m ), by non-decreasing edge weight.\n", | |
| "2. Start with a segmentation S 0 , where each vertex v i is in its own component.\n", | |
| "3. Construct $S^q$ given $S^q\u22121$ as follows. \n", | |
| "\n", | |
| "Let $v_i$ and $v_j$ denote the vertices connected by the q-th edge in the ordering, i.e., $o_q = (v_i , v_j)$. If $v_i$ and $v_j$ are in disjoint components of $S_q\u22121$ and $w(o_q)$ is small compared to the internal difference of both those components, then merge the two components otherwise do nothing.\n", | |
| "\n", | |
| "More formally, let $C_i^{q\u22121}$ be the component of $S^{q\u22121}$ containing $v_i$ and $C_j^{q\u22121}$ the component containing $v_j$. If $C_i^{q\u22121} = C_j^{q\u22121}$ and $w(o_q) \u2264 MInt(C_i^{q\u22121}, C_j^{q\u22121})$ then $S^q$ is obtained from $S^{q\u22121}$ by merging $C_i^{q\u22121}$ and $C_j^{q\u22121}$. Otherwise $S^q = S^{q\u22121}$.\n", | |
| "\n", | |
| "4..Return $S=S^m$." | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "We start by importing the required libraries" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "import networkx as nx\n", | |
| "import math\n", | |
| "import numpy as np\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "from skimage import data, io, filter, transform\n", | |
| "%matplotlib inline" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [], | |
| "prompt_number": 1 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "#show the image\n", | |
| "def show_image(image, n):\n", | |
| " plt.figure(figsize=(n,n))\n", | |
| " plt.imshow(image, cmap=plt.cm.Accent, interpolation='none')\n", | |
| " _=plt.axis('off')\n", | |
| " \n", | |
| " \n", | |
| "#show the graph\n", | |
| "def show_graph(g, **kwargs):\n", | |
| " _=nx.draw(g, pos={(i, j):(j, i) for (i, j) in g.nodes()}, edge_color='w', node_size=20, linewidths=1, **kwargs)" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [], | |
| "prompt_number": 2 | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "Here we will try to show the algorithm on a dummy generated image. Once the algorithm is properly understood, we will test it on a real image! " | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "#Generate an image here.\n", | |
| "n=8\n", | |
| "image=np.random.randint(size=(n, n), low=0, high=5)\n", | |
| "show_image(image, n)" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "metadata": {}, | |
| "output_type": "display_data", | |
| "png": "iVBORw0KGgoAAAANSUhEUgAAAdYAAAHaCAYAAAC92GghAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nElYACAkrAIT+AwvVY1WnKgyYAAAAAElFTkSuQmCC\n", | |
| "text": [ | |
| "<matplotlib.figure.Figure at 0x7f33ab48ff50>" | |
| ] | |
| } | |
| ], | |
| "prompt_number": 3 | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "Now we generate a n X n grid of nodes, simultaneously overlapping the generated image." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "g=nx.grid_2d_graph(n, n)\n", | |
| "show_image(image, n)\n", | |
| "\n", | |
| "#show the graph\n", | |
| "show_graph(g)" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "metadata": {}, | |
| "output_type": "display_data", | |
| "png": 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SzlNqhqA4djDe6opUq9MRNeJOQtqF1RvLsYPxzH/9PUYPHsyxg/HKdl+/pgy8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7hw4QIuLi6K/zgEgGM7R4InBJO8OZnQ6aEAtO/Wnic+NX99Lvt4NpHRkc32N3nhZCYvnGy27UzC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\nuXl3YNmX/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| |
| "text": [ | |
| "<matplotlib.figure.Figure at 0x7f33d076add0>" | |
| ] | |
| } | |
| ], | |
| "prompt_number": 4 | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "The nodes need to be connected to all the 8 neighbours. I did this with a hefty peice of code here!\n", | |
| "\n", | |
| "Along with the above requirement, we also need to get the weights there. As discussed above, the weights need to be a measure of dissimilarity between the two pixels of an edge." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "#The eucledian distance is a good measure of dissimilarity.\n", | |
| "def diff_dummy(x,y,x2,y2):\n", | |
| " return np.sqrt(np.square(image[x,y]-image[x2,y2]))\n", | |
| "\n", | |
| "for random_node in g.edges():\n", | |
| " x=random_node[0][0]\n", | |
| " y=random_node[0][1]\n", | |
| " x1=random_node[1][0]\n", | |
| " y1=random_node[1][1]\n", | |
| " g.add_edge(random_node[0], random_node[1], w=diff_dummy(x,y,x1,y1))\n", | |
| " \n", | |
| "for node in g.nodes():\n", | |
| " x,y=node\n", | |
| " if x>0 and y>0:\n", | |
| " g.add_edge(node,(x-1,y-1), w=diff_dummy(x,y,x-1,y-1))\n", | |
| " \n", | |
| " if x<n-1 and y<n-1:\n", | |
| " g.add_edge(node,(x+1,y+1), w=diff_dummy(x,y,x+1,y+1))\n", | |
| " \n", | |
| " if y>=1 and y<=n-1 and x<n-1:\n", | |
| " g.add_edge(node,(x+1,y-1), w=diff_dummy(x,y,x+1,y-1))" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [], | |
| "prompt_number": 5 | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "Now we have obtained the correct output!" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "#show the image\n", | |
| "show_image(image, n)\n", | |
| "#show the graph\n", | |
| "show_graph(g)" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "metadata": {}, | |
| "output_type": "display_data", | |
| "png": 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luDobqqLKcHU2VEXlcXU2VEWV4SpRrV1u9r4Bf7cErg0WTSUv+xy60DZOh6oo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\nlwAAAABJRU5ErkJggg==\n", | |
| "text": [ | |
| "<matplotlib.figure.Figure at 0x7f33a9d03910>" | |
| ] | |
| } | |
| ], | |
| "prompt_number": 6 | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "Now comes the algorithmic part. We need to start from a empty graph which has nothing but nXn nodes in it. Once we have that, we will try to follow the steps one by one." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "#generate a new graph G that with the nodes like g but no edges to start with.\n", | |
| "G=nx.Graph()\n", | |
| "G.add_nodes_from(g.nodes())\n", | |
| "\n", | |
| "#show the image\n", | |
| "show_image(image, n)\n", | |
| "\n", | |
| "#show the graph\n", | |
| "show_graph(G)" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "metadata": {}, | |
| "output_type": "display_data", | |
| "png": 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ltsLWlBdTlQmdwnkpKirCx8exe3F2djY7fv6ZRXUN9+JHTp6Eyy8nNLTtcrvV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\n8REZz6EAAAAASUVORK5CYII=\n", | |
| "text": [ | |
| "<matplotlib.figure.Figure at 0x7f33a99b8510>" | |
| ] | |
| } | |
| ], | |
| "prompt_number": 7 | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "We need to have a threshold function that works here. A threshold is defined only for a component. Once a component is merged with the other one, we change the threshold of the new component by adding it with a term called c/k... here c is the size of the new component that born just now and k is a user defined constant." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "threshold={}\n", | |
| "list_of_conn_components=nx.connected_components(G)\n", | |
| "for i in list_of_conn_components:\n", | |
| " threshold[max(i)]=1" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [], | |
| "prompt_number": 8 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "print(threshold[(7,3)])" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "stream": "stdout", | |
| "text": [ | |
| "1\n" | |
| ] | |
| } | |
| ], | |
| "prompt_number": 9 | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "Now comes the algorithmic part:\n", | |
| "\n", | |
| "Our algorithm is very much alike the Kruksal's method of finding the MST.\n", | |
| "\n", | |
| "1. Sort E into \u03c0 = (o 1 , . . . , o m ), by non-decreasing edge weight.\n", | |
| "2. Start with a segmentation S 0 , where each vertex v i is in its own component.\n", | |
| "3. Construct $S^q$ given $S^q\u22121$ as described earlier." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "for connected_edges in sorted(g.edges(data = True), key = lambda edge: edge[2]['w']):\n", | |
| " #here we are checking if the 2 nodes of the edges taken one at a time lie in the same\n", | |
| " #connected component or not.\n", | |
| " component_a=nx.node_connected_component(G, connected_edges[0])\n", | |
| " component_b=nx.node_connected_component(G, connected_edges[1])\n", | |
| " edge_weight=connected_edges[2]['w']\n", | |
| " \n", | |
| " if max(component_a)!=max(component_b):\n", | |
| " #if they are not, then we go for the weights lesser than the threshold.\n", | |
| " \n", | |
| " if (edge_weight<=min(threshold[max(component_a)], threshold[max(component_b)])):\n", | |
| " \n", | |
| " #if they are lesser than the threshold, we connect them.\n", | |
| " G.add_edge(connected_edges[0],connected_edges[1]) \n", | |
| " # both component_a and component_b are same now.\n", | |
| " threshold[max(component_a)] += 0.02*len(component_a)" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [], | |
| "prompt_number": 10 | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "The result of this simple algorithm is here:" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "#show the image\n", | |
| "show_image(image, n)\n", | |
| "\n", | |
| "#show the graph\n", | |
| "show_graph(G)" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "metadata": {}, | |
| "output_type": "display_data", | |
| "png": 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Yl0tGXMIGFdvFaDRy+PBhpk+fDkBpaSnr16/n7Nmz5OXlMWXKFDp16lSvsvLz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\nXNvT/p/hAAAAAElFTkSuQmCC\n", | |
| "text": [ | |
| "<matplotlib.figure.Figure at 0x7f33a9bcae50>" | |
| ] | |
| } | |
| ], | |
| "prompt_number": 11 | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "The above code just marks the basics that this algorithm is based on. For a real image, we have to work on smoothning and some small components compensation at the end. But they are largely small things. The conceptual part was this only." | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "The threshold is defined for each component. That is, the componenets need to change their weights. That is their internal weights go on increasing with the addition of c/k. \n", | |
| "\n", | |
| "This analogically means that the component gets reluctant to add more nodes into itself with its increment of size." | |
| ] | |
| }, | |
| { | |
| "cell_type": "heading", | |
| "level": 2, | |
| "metadata": {}, | |
| "source": [ | |
| "Let's work on a real image." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "#load an image here\n", | |
| "image=io.imread('cow.png')\n", | |
| "\n", | |
| "#choose the size to which the image has to be resized\n", | |
| "n=80\n", | |
| "\n", | |
| "#resize the image into the required dimension.\n", | |
| "image=transform.resize(image,(n,n))\n", | |
| "\n", | |
| "#separate out the three components, smoothening each one inturn\n", | |
| "r=image[:,:,0]\n", | |
| "filtered_image_r=filter.gaussian_filter(r, sigma=0.8)\n", | |
| "g=image[:,:,1]\n", | |
| "filtered_image_g=filter.gaussian_filter(g, sigma=0.8)\n", | |
| "b=image[:,:,2]\n", | |
| "filtered_image_b=filter.gaussian_filter(b, sigma=0.8)\n", | |
| "\n", | |
| "#Weight calculation for a color image\n", | |
| "def diff_color(x, y, x2, y2):\n", | |
| " return np.sqrt(\n", | |
| " np.square(filtered_image_r[x,y]-filtered_image_r[x2,y2])\n", | |
| " +np.square(filtered_image_g[x,y]-filtered_image_g[x2,y2])\n", | |
| " +np.square(filtered_image_b[x,y]-filtered_image_b[x2,y2]))" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [], | |
| "prompt_number": 12 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "g=nx.grid_2d_graph(n, n)\n", | |
| "\n", | |
| "#again we need to connect each node with all its 8 neighbours.\n", | |
| "for random_node in g.edges():\n", | |
| " x=random_node[0][0]\n", | |
| " y=random_node[0][1]\n", | |
| " x1=random_node[1][0]\n", | |
| " y1=random_node[1][1]\n", | |
| " g.add_edge(random_node[0], random_node[1], w=diff_color(x,y,x1,y1))\n", | |
| " \n", | |
| "for node in g.nodes():\n", | |
| " x,y=node\n", | |
| " if x>0 and y>0:\n", | |
| " g.add_edge(node,(x-1,y-1), w=diff_color(x,y,x-1,y-1))\n", | |
| " if x<n-1 and y<n-1:\n", | |
| " g.add_edge(node,(x+1,y+1), w=diff_color(x,y,x+1,y+1))\n", | |
| " if y>=1 and y<=n-1 and x<n-1:\n", | |
| " g.add_edge(node,(x+1,y-1), w=diff_color(x,y,x+1,y-1))\n", | |
| " \n", | |
| "#show the image\n", | |
| "show_image(image, n)\n", | |
| "\n", | |
| "#show the graph\n", | |
| "show_graph(g, with_labels=False)" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "metadata": {}, | |
| "output_type": "display_data", |
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