java像素級(jí)圖像處理與識(shí)別方法

v1.0可編寫可更正java像素級(jí)圖像辦理與鑒別方法2008-06-2119:00轉(zhuǎn)載，挺不錯(cuò)的文章朋友要求幫忙做一個(gè)圖片識(shí)其余小程序，由于要用在特定的環(huán)境下，因此決定采用java語言實(shí)現(xiàn)。第一用matlab實(shí)現(xiàn)了鑒別算法的仿真，由于不過對(duì)特定的數(shù)字組合的鑒別，因此特其余簡(jiǎn)單，放棄采納比較復(fù)雜的鑒別算法，采納最一般的像素比較的鑒別算法。（假如背景噪聲比較復(fù)雜，可以考慮先濾波后鑒別）在寫java程序的時(shí)候發(fā)現(xiàn)一些問題，網(wǎng)上關(guān)于圖片像素級(jí)操作的資料不是太多，有的還不是太正確，特此寫出自己的成就與大家分享。核心類：BufferedImage，ImageIOImageIO類供給圖象讀寫接口，可以對(duì)URL，InputStream等操作，獲得圖像信息十分的方便。ImageIO在.*的包中，屬于jdk中的標(biāo)準(zhǔn)類。供給的方法有:read( )例：BufferedImageimd=(newFile(file));write( )例：(imd,"JPEG",newFile("C:\\test"+k+".gif"));etRGB(j,i);此刻我們獲得了像素，可以看出像素是一個(gè)一維數(shù)組，你假如不習(xí)慣可以考慮保存在一個(gè)二維的數(shù)組中，而后就來實(shí)行你的看家算法，什么小波變換，拉普拉斯算子，盡管來吧。怎么樣是否是很方便呢什么你憂如看不太懂，好給你一些源程序好了，包含像素分解和鑒別算法。源代碼1v1.0可編寫可更正/*Createdon2005-11-29TODOTochangethetemplateforthisgeneratedfilegotoWindow-Preferences-Java-CodeStyle-CodeTemplates*/package.*;importimportimport.*;importimportimport.*;publicclassMyImage{BufferedImageimd;mp");if"));=newim[k].getWidth(null);=newim[k].getHeight(null);2v1.0可編寫可更正pix=newint[iw*ih];etRGB(j,i);if(pix[i*(iw)+j]==-1)pix[i*(iw)+j]=0;elsepix[i*(iw)+j]=1;x[k]=x[k]+pix[i*(iw)+j];}}獲得像般配的數(shù)字。intr=(pix);(r);"x="+x[k]);}}catch(Exceptione){( );}3v1.0可編寫可更正return( );}數(shù)字模板0-9staticint[][]value={//num0;{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,1,1,0,0,1,1,0,0,0,1,1,0,0,0,0,1,1,0,0,1,1,0,0,0,0,1,1,0,0,1,1,0,0,0,0,1,1,0,0,1,1,0,0,0,0,1,1,0,0,0,1,1,0,0,1,1,0,0,4v1.0可編寫可更正0,0,0,1,1,1,1,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},//num1{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,1,1,0,0,0,5v1.0可編寫可更正0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},//num2,//num3,//num4,//num56v1.0可編寫可更正,//num6,//num7,//num8,//num9};圖像像素相減取絕對(duì)值獲得最小熵的結(jié)果。publicintgetMatchNum(int[]pix){intresult=-1;inttemp=100;intx;for(intk=0;k<=9;k++){x=0;for(inti=0;i7v1.0可編寫可更正x=x+(pix[i]-value[k][i]);}/*for(inta=0;a