package?com.example.nicesky.idphoto_opencv330_jni.java.practice;

import?android.graphics.Bitmap;
import?com.example.nicesky.idphoto_opencv330_jni.java.L;

import?org.opencv.android.Utils;
import?org.opencv.core.CvType;
import?org.opencv.core.Mat;
import?org.opencv.core.Rect;
import?org.opencv.core.Size;
import?org.opencv.imgcodecs.Imgcodecs;
import?org.opencv.imgproc.Imgproc;

/**
?*?Created?by?fairytale110@foxmail.com?on?2018/5/17.
?*?com.example.nicesky.idphoto_opencv330_jni.java.practice
?*?IdPhoto_OpenCV330_Jni
?*?DEscriptION:
?*?UPDATE_BY:
?*?UIPDATE_DATE:
?*/

public?class?Practice?{
????private?static?String?TAG?=?“Practice==>?“;
????private?static?double?thresh?=?25;
????private?static?double?maxval?=?255;

????/**
?????*
?????*?@param?filePath??銀行卡圖片在SD卡的完整路徑?如?/storage/emulated/0/img_credit.png
?????*?@return
?????*/
????public?static?Bitmap?getNumImg（String?filePath）?{
????????//Bitmap?srcBtimap?=?BitmapFactory.decodeFile（fileName）;

????????//讀取圖像
????????Mat?srcMat?=?Imgcodecs.imread（filePath）;
????????//?Mat?srcMat?=?new?Mat（srcBtimap.getHeight（）srcBtimap.getWidth（）?CvType.CV_8UC3）;
????????//?Utils.bitmapToMat（srcBtimapsrcMat）;

????????Mat?dsstMat?=?new?Mat（srcMat.height（）?srcMat.width（）?CvType.CV_8UC3）;
????????//灰度，，黑白照
????????Imgproc.cvtColor（srcMat?dsstMat?Imgproc.COLOR_RGB2GRAY）;

????????//二值化處理?，只留兩個(gè)值，黑白
????????Mat?binaryMat?=?new?Mat（dsstMat.height（）?dsstMat.width（）?CvType.CV_8UC1）;
????????Imgproc.threshold（dsstMat?binaryMat?thresh?maxval?Imgproc.THRESH_BINARY）;

????????//使用3*3的圖片去腐蝕
????????Mat?erodeMat?=?new?Mat（）;
????????Mat?element?=?Imgproc.getStructuringElement（Imgproc.MORPH_RECT?new?Size（3?3））;
????????Imgproc.erode（binaryMat?erodeMat?element）;

????????//遍歷獲取和修改像素值
????????//二值圖片當(dāng)成一個(gè)二維矩陣就可以了雙重循環(huán)使用get方法獲取像素點(diǎn)使用put方法修改像素點(diǎn)
???????//?6.過濾和切割
????????/**
????????過濾和切割要找到一個(gè)開始行或列結(jié)束行或列這就有一個(gè)簡(jiǎn)單的算法.
????????????????該算法從第一行開始遍歷
????????????????統(tǒng)計(jì)每一行的像素點(diǎn)值符合閾值的個(gè)數(shù)再根據(jù)個(gè)數(shù)判斷該點(diǎn)是否為邊界.
????????????????找到后過濾和切割自然就很簡(jiǎn)單了直接創(chuàng)建個(gè)該范圍的新的Mat對(duì)象.*/
????????Mat?imgSrc?=?new?Mat（）;
????????Imgproc.erode（binaryMat?imgSrc?element）;
????????int?a?=?0;
????????int?b?=?imgSrc.height（）;
????????int?state?=?0;
????????int?imgN?=?5;
????????for?（int?y?=?0;?y?????????????int?count?=?0;
????????????for?（int?x?=?0;?x?????????????????//?得到該行像素點(diǎn)的值
????????????????byte[]?data?=?new?byte[1];
????????????????imgSrc.get（y?x?data）;
????????????????if?（data[0]?==?0）
????????????????????count?=?count?+?1;
????????????}
????????????if?（state?==?0）//?還未到有效行
????????????{
????????????????if?（count?>=?150）//?找到了開始行
????????????????{//?有效行允許十個(gè)像素點(diǎn)的噪聲
????????????????????a?=?y;
????????????????????state?=?1;
????????????????}
????????????}?else?if?（state?==?1）?{
????????????????if?（count?<=?100）//?找到了結(jié)束行
????????????????{//?有效行允許十個(gè)像素點(diǎn)的噪聲
????????????????????b?=?y;
????????????????????state?=?2;
???????????

?屬性????????????大小?????日期????時(shí)間???名稱
-----------?---------??----------?-----??----
?????文件??????872553??2018-05-17?17:00??img_creditcard.png
?????文件????????4225??2018-05-18?11:44??Practice.java