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<html><head> <meta HTTP-EQUIV="Content-Type" CONTENT="text/html;charset=ISO-8859-1"> <title>ocr_fun.m</title><link rel="stylesheet" type="text/css" href="../../../m-syntax.css"></head><body><code><span class=defun_kw>function</span> <span class=defun_name>ocr_fun</span>(<span class=defun_in>data</span>)<br><span class=h1>% OCR_FUN Calls OCR classifier and displays result.</span><br><span class=help>%</span><br><span class=help>% <span class=help_field>Synopsis:</span></span><br><span class=help>% ocr_fun(data)</span><br><span class=help>% </span><br><span class=help>% <span class=help_field>Description:</span></span><br><span class=help>% This function classifies images of characters stored as columns </span><br><span class=help>% of the matrix data.X. The output is displayed in a grid 5 x 10.</span><br><span class=help>%</span><br><span class=help>% <span class=help_field>Input:</span></span><br><span class=help>% data.X [dim x (5*10)] Input images store as column vectors.</span><br><span class=help>% The images are assumed to be taken from grid 5x10.</span><br><span class=help>%</span><br><hr><span class=help1>% <span class=help1_field>(c)</span> Statistical Pattern Recognition Toolbox, (C) 1999-2003,</span><br><span class=help1>% Written by Vojtech Franc and Vaclav Hlavac,</span><br><span class=help1>% <a href="http://www.cvut.cz">Czech Technical University Prague</a>,</span><br><span class=help1>% <a href="http://www.feld.cvut.cz">Faculty of Electrical engineering</a>,</span><br><span class=help1>% <a href="http://cmp.felk.cvut.cz">Center for Machine Perception</a></span><br><br><span class=help1>% <span class=help1_field>Modifications:</span></span><br><span class=help1>% 04-jun-2004, VF</span><br><span class=help1>% 09-sep-2003, VF</span><br><br><hr><span class=comment>% loads the multi-class SVM model </span><br>OCRFileName = <span class=quotes>'ocrmodel.mat'</span>;<br>ocr = load( OCRFileName );<br><br><span class=comment>% make sure that only the filled subwindows will be classified</span><br>filled_inx = find( sum(data.X) ~= 0);<br><span class=keyword>if</span> isempty(filled_inx), <span class=jump>return</span>; <span class=keyword>end</span><br>y = -ones(1,length(data.X)); <span class=comment>% non-filled subwindows are labeled by -1</span><br><br><span class=comment>% classify filled subwindows</span><br><span class=comment>%-------------------------------------------------------</span><br>[y(filled_inx),dfce] = <span class=eval>feval</span>( ocr.fun, data.X(:,filled_inx), ocr);<br><br><span class=comment>% displays results</span><br><span class=comment>%-------------------------------------------------------</span><br><span class=graph>figure</span>(10); <span class=graph>clf</span>;<br><br><span class=comment>% plot grid 5 x 10 </span><br><span class=graph>axis</span> equal;<br><span class=graph>axis</span>([0 1 0 0.5]);<br>hold on;<br><span class=graph>plot</span>( [ 0 0 1 1 0 ], [ 0 .5 .5 0 0 ] );<br><span class=keyword>for</span> i = 1:9, <span class=graph>plot</span>( [i/10 i/10],[0 .5] ); <span class=keyword>end</span><br><span class=keyword>for</span> i = 1:4, <span class=graph>plot</span>( [0 1],[i/10 i/10] ); <span class=keyword>end</span><br><br><span class=comment>% display recognized numerals</span><br><span class=keyword>for</span> i=1:5,<br> <span class=keyword>for</span> j = 1:10,<br> inx = j+(i-1)*10;<br> <span class=keyword>if</span> y(inx) ~= -1,<br> character = ocr.labels(y(inx)); <br> <br> h=text(0.05+(j-1)/10,-0.05+(5-i+1)/10,character);<br> <span class=graph>set</span>(h,<span class=quotes>'fontsize'</span>,25,<span class=quotes>'VerticalAlignment'</span>,<span class=quotes>'middle'</span>,...<br> <span class=quotes>'HorizontalAlignment'</span>,<span class=quotes>'center'</span>);<br> <span class=keyword>end</span><br> <span class=keyword>end</span><br><span class=keyword>end</span><br><br><span class=jump>return</span>;<br><span class=comment>% EOF</span><br></code>?? 快捷鍵說明
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