如何使黑板文本显得更清晰使用MATLAB？
如果我想让最终的图像更清晰一些，那么我应该放什么样的滤镜呢？ 我的意思是只有两个不同的颜色，一个是白板，一个是白板。 
当涉及识别图像中的文字时，最好使用“ 笔画宽度变换” 。
下面是我在图片上获得的一个小结果（基本变换+连接的组件不带过滤）： 
我的mex实现基于这里的代码
#include "mex.h" #include <vector> #include <map> #include <set> #include <algorithm> #include <math.h> using namespace std; #define PI 3.14159265 struct Point2d { int x; int y; float SWT; }; struct Point2dFloat { float x; float y; }; struct Ray { Point2d p; Point2d q; std::vector<Point2d> points; }; void strokeWidthTransform(const float * edgeImage, const float * gradientX, const float * gradientY, bool dark_on_light, float * SWTImage, int h, int w, std::vector<Ray> & rays) { // First pass float prec = .05f; for( int row = 0; row < h; row++ ){ const float* ptr = edgeImage + row*w; for ( int col = 0; col < w; col++ ){ if (*ptr > 0) { Ray r; Point2d p; px = col; py = row; rp = p; std::vector<Point2d> points; points.push_back(p); float curX = (float)col + 0.5f; float curY = (float)row + 0.5f; int curPixX = col; int curPixY = row; float G_x = gradientX[ col + row*w ]; float G_y = gradientY[ col + row*w ]; // normalize gradient float mag = sqrt( (G_x * G_x) + (G_y * G_y) ); if (dark_on_light){ G_x = -G_x/mag; G_y = -G_y/mag; } else { G_x = G_x/mag; G_y = G_y/mag; } while (true) { curX += G_x*prec; curY += G_y*prec; if ((int)(floor(curX)) != curPixX || (int)(floor(curY)) != curPixY) { curPixX = (int)(floor(curX)); curPixY = (int)(floor(curY)); // check if pixel is outside boundary of image if (curPixX < 0 || (curPixX >= w) || curPixY < 0 || (curPixY >= h)) { break; } Point2d pnew; pnew.x = curPixX; pnew.y = curPixY; points.push_back(pnew); if ( edgeImage[ curPixY*w+ curPixX ] > 0) { rq = pnew; // dot product float G_xt = gradientX[ curPixY*w + curPixX ]; float G_yt = gradientY[ curPixY*w + curPixX ]; mag = sqrt( (G_xt * G_xt) + (G_yt * G_yt) ); if (dark_on_light){ G_xt = -G_xt/mag; G_yt = -G_yt/mag; } else { G_xt = G_xt/mag; G_yt = G_yt/mag; } if (acos(G_x * -G_xt + G_y * -G_yt) < PI/2.0 ) { float length = sqrt( ((float)rqx - (float)rpx)*((float)rqx - (float)rpx) + ((float)rqy - (float)rpy)*((float)rqy - (float)rpy)); for (std::vector<Point2d>::iterator pit = points.begin(); pit != points.end(); pit++) { float* pSWT = SWTImage + w * pit->y + pit->x; if (*pSWT < 0) { *pSWT = length; } else { *pSWT = std::min(length, *pSWT); } } r.points = points; rays.push_back(r); } break; } } } } ptr++; } } } bool Point2dSort(const Point2d &lhs, const Point2d &rhs) { return lhs.SWT < rhs.SWT; } void SWTMedianFilter(float * SWTImage, int h, int w, std::vector<Ray> & rays, float maxWidth = -1 ) { for (std::vector<Ray>::iterator rit = rays.begin(); rit != rays.end(); rit++) { for (std::vector<Point2d>::iterator pit = rit->points.begin(); pit != rit->points.end(); pit++) { pit->SWT = SWTImage[ w*pit->y + pit->x ]; } std::sort(rit->points.begin(), rit->points.end(), &Point2dSort); //std::nth_element( rit->points.begin(), rit->points.end(), rit->points.size()/2, &Point2dSort ); float median = (rit->points[rit->points.size()/2]).SWT; if ( maxWidth > 0 && median >= maxWidth ) { median = -1; } for (std::vector<Point2d>::iterator pit = rit->points.begin(); pit != rit->points.end(); pit++) { SWTImage[ w*pit->y + pit->x ] = std::min(pit->SWT, median); } } } typedef std::vector< std::set<int> > graph_t; // graph as a list of neighbors per node void connComp( const graph_t& g, std::vector<int>& c, int i, int l ) { // starting from node i labe this conn-comp with label l if ( i < 0 || i > g.size() ) { return; } std::vector< int > stack; // push i stack.push_back(i); c[i] = l; while ( ! stack.empty() ) { // pop i = stack.back(); stack.pop_back(); // go over all nieghbors for ( std::set<int>::const_iterator it = g[i].begin(); it != g[i].end(); it++ ) { if ( c[*it] < 0 ) { stack.push_back( *it ); c[ *it ] = l; } } } } int findNextToLabel( const graph_t& g, const vector<int>& c ) { for ( int i = 0 ; i < c.size(); i++ ) { if ( c[i] < 0 ) { return i; } } return c.size(); } int connected_components(const graph_t& g, vector<int>& c) { // check for empty graph! if ( g.empty() ) { return 0; } int i = 0; int num_conn = 0; do { connComp( g, c, i, num_conn ); num_conn++; i = findNextToLabel( g, c ); } while ( i < g.size() ); return num_conn; } std::vector< std::vector<Point2d> > findLegallyConnectedComponents(const float* SWTImage, int h, int w, std::vector<Ray> & rays) { std::map<int, int> Map; std::map<int, Point2d> revmap; std::vector<std::vector<Point2d> > components; // empty int num_vertices = 0, idx = 0; graph_t g; // Number vertices for graph. Associate each point with number for( int row = 0; row < h; row++ ){ for (int col = 0; col < w; col++ ){ idx = col + w * row; if (SWTImage[idx] > 0) { Map[idx] = num_vertices; Point2d p; px = col; py = row; revmap[num_vertices] = p; num_vertices++; std::set<int> empty; g.push_back(empty); } } } if ( g.empty() ) { return components; // nothing to do with an empty graph... } for( int row = 0; row < h; row++ ){ for (int col = 0; col < w; col++ ){ idx = col + w * row; if ( SWTImage[idx] > 0) { // check pixel to the right, right-down, down, left-down int this_pixel = Map[idx]; float thisVal = SWTImage[idx]; if (col+1 < w) { float right = SWTImage[ w*row + col + 1 ]; if (right > 0 && (thisVal/right <= 3.0 || right/thisVal <= 3.0)) { g[this_pixel].insert( Map[ w*row + col + 1 ] ); g[ Map[ w*row + col + 1 ] ].insert( this_pixel ); //boost::add_edge(this_pixel, map.at(row * SWTImage->width + col + 1), g); } } if (row+1 < h) { if (col+1 < w) { float right_down = SWTImage[ w*(row+1) + col + 1 ]; if (right_down > 0 && (thisVal/right_down <= 3.0 || right_down/thisVal <= 3.0)) { g[ this_pixel ].insert( Map[ w*(row+1) + col + 1 ] ); g[ Map[ w*(row+1) + col + 1 ] ].insert(this_pixel); // boost::add_edge(this_pixel, map.at((row+1) * SWTImage->width + col + 1), g); } } float down = SWTImage[ w*(row+1) + col ]; if (down > 0 && (thisVal/down <= 3.0 || down/thisVal <= 3.0)) { g[ this_pixel ].insert( Map[ w*(row+1) + col ] ); g[ Map[ w*(row+1) + col ] ].insert( this_pixel ); //boost::add_edge(this_pixel, map.at((row+1) * SWTImage->width + col), g); } if (col-1 >= 0) { float left_down = SWTImage[ w*(row+1) + col - 1 ]; if (left_down > 0 && (thisVal/left_down <= 3.0 || left_down/thisVal <= 3.0)) { g[ this_pixel ].insert( Map[ w*(row+1) + col - 1 ] ); g[ Map[ w*(row+1) + col - 1 ] ].insert( this_pixel ); //boost::add_edge(this_pixel, map.at((row+1) * SWTImage->width + col - 1), g); } } } } } } std::vector<int> c(num_vertices, -1); int num_comp = connected_components(g, c); components.reserve(num_comp); //std::cout << "Before filtering, " << num_comp << " components and " << num_vertices << " vertices" << std::endl; for (int j = 0; j < num_comp; j++) { std::vector<Point2d> tmp; components.push_back( tmp ); } for (int j = 0; j < num_vertices; j++) { Point2d p = revmap[j]; (components[c[j]]).push_back(p); } return components; } enum { EIN = 0, GXIN, GYIN, DOLFIN, MAXWIN, NIN }; void mexFunction( int nout, mxArray* pout[], int nin, const mxArray* pin[] ) { // // make sure images are input in transposed so that they are arranged row-major in memory // mxAssert( nin == NIN, "wrong number of inputs" ); mxAssert( nout > 1, "only one output" ); int h = mxGetN( pin[EIN] ); // inputs are transposed! int w = mxGetM( pin[EIN] ); mxAssert( mxIsClass( pin[EIN], mxSINGLE_CLASS ) && h == mxGetN( pin[EIN] ) && w == mxGetM( pin[EIN] ), "edge map incorrect"); mxAssert( mxIsClass( pin[GXIN], mxSINGLE_CLASS ) && h == mxGetN( pin[GXIN] ) && w == mxGetM( pin[GXIN] ), "edge map incorrect"); mxAssert( mxIsClass( pin[GYIN], mxSINGLE_CLASS ) && h == mxGetN( pin[GYIN] ) && w == mxGetM( pin[GYIN] ), "edge map incorrect"); const float * edgeImage = (float*) mxGetData( pin[EIN] ); const float * gradientX = (float*) mxGetData( pin[GXIN] ); const float * gradientY = (float*) mxGetData( pin[GYIN] ); bool dark_on_light = mxGetScalar( pin[DOLFIN] ) != 0 ; float maxWidth = mxGetScalar( pin[MAXWIN] ); // allocate output pout[0] = mxCreateNumericMatrix( w, h, mxSINGLE_CLASS, mxREAL ); float * SWTImage = (float*) mxGetData( pout[0] ); // set SWT to -1 for ( int i = 0 ; i < w*h; i++ ) { SWTImage[i] = -1; } std::vector<Ray> rays; strokeWidthTransform ( edgeImage, gradientX, gradientY, dark_on_light, SWTImage, h, w, rays ); SWTMedianFilter ( SWTImage, h, w, rays, maxWidth ); // connected components if ( nout > 1 ) { // Calculate legally connect components from SWT and gradient image. // return type is a vector of vectors, where each outer vector is a component and // the inner vector contains the (y,x) of each pixel in that component. std::vector<std::vector<Point2d> > components = findLegallyConnectedComponents(SWTImage, h, w, rays); pout[1] = mxCreateNumericMatrix( w, h, mxSINGLE_CLASS, mxREAL ); float* pComp = (float*) mxGetData( pout[1] ); for ( int i = 0 ; i < w*h; i++ ) { pComp[i] = 0; } for ( int ci = 0 ; ci < components.size(); ci++ ) { for ( std::vector<Point2d>::iterator it = components[ci].begin() ; it != components[ci].end(); it++ ) { pComp[ w * it->y + it->x ] = ci + 1; } } } }
Matlab函数调用stroke-width-transform（SWT）mex-file：
function [swt swtcc] = SWT( img, dol, maxWidth ) if size( img, 3 ) == 3 img = rgb2gray(img); end img = im2single(img); edgeMap = single( edge( img, 'canny', .15 ) ); img = imfilter( img, fspecial('gauss',[5 5], 0.3*(2.5-1)+.8) ); gx = imfilter( img, fspecial('prewitt')' ); %//' gy = imfilter( img, fspecial('prewitt') ); gx = single(medfilt2( gx, [3 3] )); gy = single(medfilt2( gy, [3 3] )); [swt swtcc] = swt_mex( edgeMap.', gx.', gy.', dol, maxWidth ); %//' swt = swt'; %//' swtcc = double(swtcc'); %//'
尝试这个 ：
I = imread('...'); % Your board image ThreshConstant = 1; % Try to vary this constant. bw = im2bw(I , ThreshConstant * graythresh(I)); % Black-white image SegmentedImg = I.*repmat(uint8(bw), [1 1 3]);
只要做imshow(bw); 你会有一个2彩色图像通常很好地分割。
如果阈值太大，尝试使用ThreshConstant将阈值调整为0.5至1.5。
或者你可以试试这个
im = imread('http://i.imgur.com/uJIXp13.jpg'); %the image posted above im2=rgb2gray(im); maxp=uint16(max(max(im2))); minp=uint16(min(min(im2))); bw=im2bw(im2,(double(minp+maxp))/(2*255)); %the threshold as alexandre said, but with the min max idensity as threshold bw=~bw; % you need to reverse from black font - whit letters to black letters white font :P imshow(bw)
这应该是结果
记住，你可以自适应地使用这个技术的窗口，每次find窗口的阈值，以获得最佳结果。
