diff --git a/src/main/java/com/yuxue/util/ImageUtil.java b/src/main/java/com/yuxue/util/ImageUtil.java
index 26cc0ec4..65b29d09 100644
--- a/src/main/java/com/yuxue/util/ImageUtil.java
+++ b/src/main/java/com/yuxue/util/ImageUtil.java
@@ -24,6 +24,7 @@ import org.opencv.imgproc.Imgproc;
 
 import com.google.common.collect.Lists;
 import com.google.common.collect.Maps;
+import com.yuxue.enumtype.PlateColor;
 
 
 /**
@@ -69,8 +70,8 @@ public class ImageUtil {
     public static void main(String[] args) {
         Instant start = Instant.now();
         String tempPath = DEFAULT_BASE_TEST_PATH + "test/";
-        String filename = tempPath + "/100_yuantu.jpg";
-        filename = tempPath + "/100_yuantu3.jpg";
+         String filename = tempPath + "/100_yuantu.jpg";
+        filename = tempPath + "/100_yuantu1.jpg";
         // filename = tempPath + "/109_crop_0.png";
 
         Mat src = Imgcodecs.imread(filename);
@@ -79,10 +80,10 @@ public class ImageUtil {
 
         Mat gsMat = ImageUtil.gaussianBlur(src, debug, tempPath);
 
-        Mat grey = ImageUtil.grey(gsMat, debug, tempPath);
+        Mat gray = ImageUtil.gray(gsMat, debug, tempPath);
 
-        Mat sobel = ImageUtil.sobel(grey, debug, tempPath);
-        // Mat sobel = ImageUtil.scharr(grey, debug, tempPath);
+        Mat sobel = ImageUtil.sobel(gray, debug, tempPath);
+        // Mat sobel = ImageUtil.scharr(gray, debug, tempPath);
 
         Mat threshold = ImageUtil.threshold(sobel, debug, tempPath);
 
@@ -92,17 +93,32 @@ public class ImageUtil {
 
         Vector<Mat> rects = ImageUtil.screenBlock(src, contours, debug, tempPath);
 
+        PlateUtil.loadSvmModel("D:/PlateDetect/train/plate_detect_svm/svm2.xml");
+        PlateUtil.loadAnnModel("D:/PlateDetect/train/chars_recognise_ann/ann.xml");
+        
         Vector<Mat> dst = new Vector<Mat>();
-        PalteUtil.hasPlate(rects, dst, "D:/PlateDetect/train/plate_detect_svm/svm2.xml", debug, tempPath);
-
+        PlateUtil.hasPlate(rects, dst, debug, tempPath);
+        
         System.err.println("识别到的车牌数量：" + dst.size());
+        dst.stream().forEach(inMat -> {
+            PlateColor color = PlateUtil.getPlateColor(inMat, true, debug, tempPath);
+            System.err.println(color.desc);
+
+            Vector<Mat> charMat = new Vector<Mat>();
+            PlateUtil.charsSegment(inMat, color, charMat, debug, tempPath);
+            
+        });
+        
+        /*String filename = tempPath + "/hsvMat_1590994270425.jpg";
+        Mat src = Imgcodecs.imread(filename);
+        Vector<Mat> charMat = new Vector<Mat>();
+        PlateUtil.charsSegment(src, PlateColor.BLUE, charMat, true, tempPath);*/
 
         // ImageUtil.rgb2Hsv(src, debug, tempPath);
         // ImageUtil.getHSVValue(src, debug, tempPath);
 
         Instant end = Instant.now();
         System.err.println("总耗时：" + Duration.between(start, end).toMillis());
-
     }
 
 
@@ -131,7 +147,7 @@ public class ImageUtil {
      * @param tempPath
      * @return
      */
-    public static Mat grey(Mat inMat, Boolean debug, String tempPath) {
+    public static Mat gray(Mat inMat, Boolean debug, String tempPath) {
         Mat dst = new Mat();
         Imgproc.cvtColor(inMat, dst, Imgproc.COLOR_BGR2GRAY);
         if (debug) {
@@ -291,7 +307,6 @@ public class ImageUtil {
         // CV_CHAIN_APPROX_NONE 保存物体边界上所有连续的轮廓点到contours向量内
         Imgproc.findContours(inMat, contours, hierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_NONE);
 
-        // 在小连接处分割轮廓
         if (debug) {
             Mat result = new Mat();
             src.copyTo(result); //  复制一张图，不在原图上进行操作，防止后续需要使用原图
@@ -346,7 +361,7 @@ public class ImageUtil {
                 Mat img_crop = new Mat();
                 Imgproc.getRectSubPix(src, rect_size, mr.center, img_crop);
                 if (debug) {
-                    Imgcodecs.imwrite(tempPath + debugMap.get("crop") + "_crop_" + j + ".png", img_crop);
+                    // Imgcodecs.imwrite(tempPath + debugMap.get("crop") + "_crop_" + j + ".png", img_crop);
                 }
                 // 处理切图，调整为指定大小
                 Mat resized = new Mat(HEIGHT, WIDTH, TYPE);
@@ -424,7 +439,7 @@ public class ImageUtil {
         Core.merge(hsvSplit, dst);
 
         if (debug) {
-            Imgcodecs.imwrite(tempPath + "hsvMat_"+System.currentTimeMillis()+".jpg", dst);
+            // Imgcodecs.imwrite(tempPath + "hsvMat_"+System.currentTimeMillis()+".jpg", dst);
         }
         return dst;
     }
diff --git a/src/main/java/com/yuxue/util/PalteUtil.java b/src/main/java/com/yuxue/util/PlateUtil.java
similarity index 51%
rename from src/main/java/com/yuxue/util/PalteUtil.java
rename to src/main/java/com/yuxue/util/PlateUtil.java
index c2c60414..ff3f5eb4 100644
--- a/src/main/java/com/yuxue/util/PalteUtil.java
+++ b/src/main/java/com/yuxue/util/PlateUtil.java
@@ -1,15 +1,22 @@
 package com.yuxue.util;
 
+import java.util.Arrays;
 import java.util.List;
 import java.util.Map;
+import java.util.Set;
 import java.util.Vector;
 import java.util.Map.Entry;
 import java.util.regex.Matcher;
 import java.util.regex.Pattern;
 
 import org.opencv.core.Core;
+import org.opencv.core.CvType;
 import org.opencv.core.Mat;
+import org.opencv.core.MatOfPoint;
+import org.opencv.core.Rect;
+import org.opencv.core.Scalar;
 import org.opencv.imgcodecs.Imgcodecs;
+import org.opencv.imgproc.Imgproc;
 import org.opencv.ml.ANN_MLP;
 import org.opencv.ml.SVM;
 
@@ -27,15 +34,18 @@ import com.yuxue.train.SVMTrain;
  * @author yuxue
  * @date 2020-05-28 15:11
  */
-public class PalteUtil {
-    
+public class PlateUtil {
+
     // 车牌定位处理步骤，该map用于表示步骤图片的顺序
     private static Map<String, Integer> debugMap = Maps.newLinkedHashMap();
     static {
         System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
-        
+
+        debugMap.put("platePredict", 0); 
         debugMap.put("colorMatch", 0); 
-        debugMap.put("char_threshold", 0); 
+        debugMap.put("plateThreshold", 0); 
+        debugMap.put("plateContours", 0); 
+        debugMap.put("plateCrop", 0); 
         debugMap.put("char_clearLiuDing", 0); // 去除柳钉
         debugMap.put("specMat", 0); 
         debugMap.put("chineseMat", 0);
@@ -47,6 +57,9 @@ public class PalteUtil {
             entry.setValue(index);
             index ++;
         }
+
+        /*loadSvmModel("D:/PlateDetect/train/plate_detect_svm/svm2.xml");
+        loadAnnModel("D:/PlateDetect/train/chars_recognise_ann/ann.xml");*/
     }
 
     private static SVM svm = SVM.create();
@@ -97,22 +110,17 @@ public class PalteUtil {
      */
     public static final int DEFAULT_WIDTH = 136;
     public static final int DEFAULT_HEIGHT = 36;
-    public static void hasPlate(Vector<Mat> inMat, Vector<Mat> dst, String modelPath, 
-            Boolean debug, String tempPath) {
-        loadSvmModel(modelPath);
-
+    public static void hasPlate(Vector<Mat> inMat, Vector<Mat> dst, Boolean debug, String tempPath) {
         int i = 0;
         for (Mat src : inMat) {
             if(src.rows() == DEFAULT_HEIGHT && src.cols() == DEFAULT_WIDTH) {
                 Mat samples = SVMTrain.getFeature(src);
-
                 float flag = svm.predict(samples);
-
                 if (flag == 0) {
                     dst.add(src);
                     if(debug) {
                         System.err.println("目标符合");
-                        Imgcodecs.imwrite(tempPath + "199_plate_reco_" + i + ".png", src);
+                        Imgcodecs.imwrite(tempPath + debugMap.get("platePredict") + "_platePredict" + i + ".png", src);
                     }
                     i++;
                 } else {
@@ -122,8 +130,8 @@ public class PalteUtil {
         }
         return;
     }
-    
-    
+
+
     /**
      * 判断切图车牌颜色
      * @param inMat
@@ -132,7 +140,7 @@ public class PalteUtil {
     public static PlateColor getPlateColor(Mat inMat, Boolean adaptive_minsv, Boolean debug, String tempPath) {
         // 判断阈值
         final float thresh = 0.49f;
-        
+
         if(colorMatch(inMat, PlateColor.BLUE, adaptive_minsv, debug, tempPath) > thresh) {
             return PlateColor.BLUE;
         }
@@ -145,7 +153,7 @@ public class PalteUtil {
         return PlateColor.UNKNOWN;
     }
 
-   
+
     /**
      * 颜色匹配计算
      * @param inMat
@@ -197,18 +205,161 @@ public class PalteUtil {
                 }
             }
         }
-        
+
         // 获取颜色匹配后的二值灰度图
         List<Mat> hsvSplit = Lists.newArrayList();
         Core.split(hsvMat, hsvSplit);
-        Mat grey = hsvSplit.get(2);
-        
-        float percent = (float) Core.countNonZero(grey) / (grey.rows() * grey.cols());
+        Mat gray = hsvSplit.get(2);
+
+        float percent = (float) Core.countNonZero(gray) / (gray.rows() * gray.cols());
         if (debug) {
-            Imgcodecs.imwrite(tempPath + debugMap.get("colorMatch") + "_colorMatch.jpg", grey);
+            Imgcodecs.imwrite(tempPath + debugMap.get("colorMatch") + "_colorMatch.jpg", gray);
         }
-
         return percent;
     }
 
+
+
+    /**
+     * 车牌切图，分割成单个字符切图
+     * @param inMat 输入原始图像
+     * @param charMat 返回字符切图vector
+     * @param debug
+     * @param tempPath
+     */
+    public static final int DEFAULT_ANGLE = 30; // 角度判断所用常量
+    public static void charsSegment(Mat inMat, PlateColor color, Vector<Mat> charMat, Boolean debug, String tempPath) {
+        Mat gray = new Mat();
+        Imgproc.cvtColor(inMat, gray, Imgproc.COLOR_BGR2GRAY);
+
+        Mat threshold = new Mat();
+        switch (color) {
+        case BLUE:
+            Imgproc.threshold(gray, threshold, 10, 255, Imgproc.THRESH_OTSU + Imgproc.THRESH_BINARY);
+            break;
+
+        case YELLOW:
+            Imgproc.threshold(gray, threshold, 10, 255, Imgproc.THRESH_OTSU + Imgproc.THRESH_BINARY_INV);
+            break;
+
+        case GREEN:
+            Imgproc.threshold(gray, threshold, 10, 255, Imgproc.THRESH_OTSU + Imgproc.THRESH_BINARY_INV);
+            break;
+
+        default:
+            return;
+        }
+
+        // 图片处理，降噪等
+        if (debug) {
+            Imgcodecs.imwrite(tempPath + debugMap.get("plateThreshold") + "_plateThreshold.jpg", threshold);
+        }
+
+        // 获取轮廓
+        Mat contour = new Mat();
+        threshold.copyTo(contour);
+
+        List<MatOfPoint> contours = Lists.newArrayList();
+        // 提取外部轮廓
+        Imgproc.findContours(contour, contours, new Mat(), Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_NONE);
+
+        if (debug) {
+            Mat result = new Mat();
+            inMat.copyTo(result);
+            Imgproc.drawContours(result, contours, -1, new Scalar(0, 0, 255, 255));
+            Imgcodecs.imwrite(tempPath + debugMap.get("plateContours") + "_plateContours.jpg", result);
+        }
+
+
+        Vector<Rect> rt = new Vector<Rect>();
+        for (int i = 0; i < contours.size(); i++) {
+            Rect mr = Imgproc.boundingRect(contours.get(i));
+            if (checkCharSizes(mr)) {
+                rt.add(mr);
+            }
+        }
+        if(null == rt || rt.size() <= 0) {
+            return;
+        }
+        Vector<Rect> sorted = new Vector<Rect>();
+        sortRect(rt, sorted);
+
+        Vector<Mat> dst = new Vector<Mat>();
+        for (int i = 0; i < sorted.size(); i++) {
+            Mat img_crop = new Mat(threshold, sorted.get(i));
+            img_crop = preprocessChar(img_crop);
+            dst.add(img_crop);
+            Imgcodecs.imwrite(tempPath + debugMap.get("plateCrop") + "_plateCrop_" + i + ".jpg", img_crop);
+        }
+
+        
+
+        return;
+    }
+
+    /**
+     * 字符预处理: 统一每个字符的大小
+     * 
+     * @param in
+     * @return
+     */
+    final static int CHAR_SIZE = 20;
+    private static Mat preprocessChar(Mat in) {
+        int h = in.rows();
+        int w = in.cols();
+        Mat transformMat = Mat.eye(2, 3, CvType.CV_32F);
+        int m = Math.max(w, h);
+        transformMat.put(0, 2, (m - w) / 2f);
+        transformMat.put(1, 2, (m - h) / 2f);
+
+        Mat warpImage = new Mat(m, m, in.type());
+        Imgproc.warpAffine(in, warpImage, transformMat, warpImage.size(), Imgproc.INTER_LINEAR, Core.BORDER_CONSTANT, new Scalar(0));
+
+        Mat resized = new Mat(CHAR_SIZE, CHAR_SIZE, CvType.CV_8UC3);
+        Imgproc.resize(warpImage, resized, resized.size(), 0, 0, Imgproc.INTER_CUBIC);
+
+        return resized;
+    }
+
+
+
+    /**
+     * 字符尺寸验证；去掉尺寸不符合的图块
+     * 此处计算宽高比意义不大，因为字符 1 的宽高比干扰就已经很大了
+     * @param r
+     * @return
+     */
+    public static Boolean checkCharSizes(Rect r) {
+        float minHeight = 15f;
+        float maxHeight = 35f;
+        double charAspect = r.size().width / r.size().height;
+        return charAspect <1 && minHeight <= r.size().height && r.size().height < maxHeight;
+    }
+
+
+
+    /**
+     * 将Rect按位置从左到右进行排序
+     * @param vecRect
+     * @param out
+     * @return
+     */
+    public static void sortRect(Vector<Rect> vecRect, Vector<Rect> out) {
+        Map<Integer, Integer> map = Maps.newHashMap();
+        for (int i = 0; i < vecRect.size(); ++i) {
+            map.put(vecRect.get(i).x, i);
+        }
+        Set<Integer> set = map.keySet();
+        Object[] arr = set.toArray();
+        Arrays.sort(arr);
+        for (Object key : arr) {
+            out.add(vecRect.get(map.get(key)));
+        }
+        return;
+    }
+
+
+
+
+
 }