数字图像处理 编程实现java源码

/* * @Ch11DigitRecog.java * @Version 1.0 2010.02.21 * @Author Xie-Hua Sun */ package Chapters; import java.awt.*; import java.awt.event.*; import javax.swing.*; import java.io.*; class Ch11DigitRecog extends JFrame implements ActionListener { int model, //数字代号 type, //算法型号,0:模板匹配和Bayes,1:LMSE和奖惩算法 m_num = 0; int count; int[][][] sample; double[][][] Dsample; boolean isChooseAlg, //算法选择标志 isSaved; //数据文件存储标志 String algName; public Ch11DigitRecog() { setTitle("数字图像处理-Java编程与实验 第11章 模式识别"); sample = new int[10][2][25]; Dsample = new double[10][2][25]; count = 0; model = 0; isChooseAlg = false; setMenu(); addWindowListener(new WindowAdapter() { public void windowClosing(WindowEvent e) { if(isSaved == false) if(check() == 0) save(); System.exit(0); } }); setSize(368,430); setVisible(true); } public void actionPerformed(ActionEvent e) { if(e.getSource() == recognize) //识别 { if(type == 0) result.setText(" "+ recognize()); else if(type == 1) result.setText(" "+ TwoValueBayes()); else if(type == 2) result.setText(" "+ LMSE()); else if(type == 3) result.setText(" "+ Reward_Punish()); train.setEnabled(false); num.setEnabled(false); inform.setText("使用按钮清除可擦除数字"); } else if(e.getSource() == clear) clearall(); else if(e.getSource() == train) //训练 { if(type == 0 ||type == 1) { int[] tem = character(); for(int j = 0; j < 25; j++) sample[model][m_num][j] = tem[j]; inform.setText("数字 "+model+" 的第 "+(m_num+1)+ " 个样本已完成训练.\n"+ "每个数字输入两个样本."); m_num++; m_num = m_num%2; if(model == 9) recognize.setEnabled(true); clearall(); } else { double[] dtem = CHARACTER(); for(int j = 0; j < 25; j++) Dsample[model][m_num][j] = dtem[j]; inform.setText("数字 "+model+" 的第 "+(m_num+1)+ " 个样本已完成训练.\n"+ "每个数字输入两个样本."); m_num++; m_num = m_num%2; if(model == 9) recognize.setEnabled(true); clearall(); } } else if(e.getSource() == news) //新建样本 { if(isChooseAlg) { inform.setText("按下鼠标左键并拖动, 在右边输入板中手写数字,"+ "\n"+"依次输入0 - 9数字样本"); recognize.setEnabled(false); alg.setEditable(false); train.setEnabled(true); num.setEnabled(true); clear.setEnabled(true); isSaved = false; } else JOptionPane.showMessageDialog(null, "请先选择识别算法!"); } else if(e.getSource() == save) //保存样本 save(); else if(e.getSource() == load) //载入样本 { if(isChooseAlg) { load(); isSaved = true; alg.setEnabled(false); num.setEnabled(false); inform.setText("按下鼠标左键并拖动, 在右边输入板中手写数字"); } else JOptionPane.showMessageDialog(null, "请先选择识别算法!"); } else if(e.getSource() == renew) //更改算法,初始化 { count = 0; model = 0; isChooseAlg = false; alg.setEnabled(true); recognize.setEnabled(false); clear.setEnabled(false); train.setEnabled(false); num.setEnabled(false); } else if(e.getSource() == alg) //算法选择框 { algName = (String)alg.getSelectedItem(); if(algName.equals("模板匹配算法")) type = 0; else if(algName.equals("Bayes分类器")) type = 1; else if(algName.equals("LMSE")) type = 2; else type = 3; isChooseAlg = true; } else if(e.getSource() == num) //训练选择框 model = Integer.parseInt((String)num.getSelectedItem()); else if(e.getSource() == quit) { if(isSaved == false) if(check() == 0) save(); System.exit(0); } } //标准化,将输入的数字缩放到5X5标准大小 int[] character() { int minx = 1000, miny = 1000, maxx = 0, maxy = 0; int ti, tj; int[] chr = new int[25]; int[][] temp = can.getXY(); //分别计算最小和最大的x[i],y[i] for(int i = 0; i < count; i++) { if(temp[0][i] == -1) continue; if(temp[0][i] < minx) minx = temp[0][i]; if(temp[1][i] < miny) miny = temp[1][i]; if(temp[0][i] > maxx) maxx = temp[0][i]; if(temp[1][i] > maxy) maxy = temp[1][i]; } int xlen = maxx - minx; int ylen = maxy - miny; //按比例缩放到标准大小.并计算row[i],col[i] 　 for(int i = 0; i < count; i++) { if(temp[0][i] == -1) continue; ti = (temp[1][i]-miny)*5/ylen; tj = (temp[0][i]-minx)*5/xlen; if(ti == 5) ti = 4; if(tj == 5) tj = 4; chr[ti*5+tj]++; } return chr; } //标准化,将输入的数字缩放到5X5标准大小 public double[] CHARACTER() { int minx = 1000, miny = 1000, maxx = 0, maxy = 0; int ti, tj; int[] chr = new int[25]; double[] t = new double[25]; int[][] temp = can.getXY(); //分别计算最小和最大的x[i],y[i] for(int i = 0; i < count; i++) { if(temp[0][i] == -1) continue; if(temp[0][i] < minx) minx = temp[0][i]; if(temp[1][i] < miny) miny = temp[1][i]; if(temp[0][i] > maxx) maxx = temp[0][i]; if(temp[1][i] > maxy) maxy = temp[1][i]; } int xlen = maxx - minx; int ylen = maxy - miny; //按比例缩放到标准大小.并计算row[i],col[i] 　 for(int i = 0; i < count; i++) { if(temp[0][i] == -1) continue; ti = (temp[1][i]-miny)*5/ylen; tj = (temp[0][i]-minx)*5/xlen; if(ti == 5) ti = 4; if(tj == 5) tj = 4; chr[ti*5+tj]++; } int w = xlen/5; int h = ylen/5; for(int i = 0; i < 5; i++) for(int j = 0; j < 5; j++) t[i*5+j] = chr[i*5+j]*7.0/(w*h); return t; } int recognize() { int[][] distance = new int[10][2]; int[] tem = character(); int n = 0; for(int k = 0; k < 10; k++) { for(int i = 0; i < 2; i++) { distance[k][i] = 0; for(int j = 0; j < 25; j++) distance[k][i] += Math.abs