add windows vs project

2017-11-15 01:07:41 +08:00
parent 4e28874afe
commit c48543095e
416 changed files with 14076 additions and 13 deletions
@@ -0,0 +1,107 @@
+//
+// Created by 庾金科 on 26/10/2017.
+//
+
+#ifndef SWIFTPR_NIBLACKTHRESHOLD_H
+#define SWIFTPR_NIBLACKTHRESHOLD_H
+
+
+#include <opencv2/opencv.hpp>
+using namespace cv;
+
+enum LocalBinarizationMethods{
+    BINARIZATION_NIBLACK = 0, //!< Classic Niblack binarization. See @cite Niblack1985 .
+    BINARIZATION_SAUVOLA = 1, //!< Sauvola's technique. See @cite Sauvola1997 .
+    BINARIZATION_WOLF = 2,    //!< Wolf's technique. See @cite Wolf2004 .
+    BINARIZATION_NICK = 3     //!< NICK technique. See @cite Khurshid2009 .
+};
+
+
+void niBlackThreshold( InputArray _src, OutputArray _dst, double maxValue,
+                       int type, int blockSize, double k, int binarizationMethod )
+{
+    // Input grayscale image
+    Mat src = _src.getMat();
+    CV_Assert(src.channels() == 1);
+    CV_Assert(blockSize % 2 == 1 && blockSize > 1);
+    if (binarizationMethod == BINARIZATION_SAUVOLA) {
+        CV_Assert(src.depth() == CV_8U);
+    }
+    type &= THRESH_MASK;
+    // Compute local threshold (T = mean + k * stddev)
+    // using mean and standard deviation in the neighborhood of each pixel
+    // (intermediate calculations are done with floating-point precision)
+    Mat test;
+    Mat thresh;
+    {
+        // note that: Var[X] = E[X^2] - E[X]^2
+        Mat mean, sqmean, variance, stddev, sqrtVarianceMeanSum;
+        double srcMin, stddevMax;
+        boxFilter(src, mean, CV_32F, Size(blockSize, blockSize),
+                  Point(-1,-1), true, BORDER_REPLICATE);
+        sqrBoxFilter(src, sqmean, CV_32F, Size(blockSize, blockSize),
+                     Point(-1,-1), true, BORDER_REPLICATE);
+        variance = sqmean - mean.mul(mean);
+        sqrt(variance, stddev);
+        switch (binarizationMethod)
+        {
+            case BINARIZATION_NIBLACK:
+                thresh = mean + stddev * static_cast<float>(k);
+
+                break;
+            case BINARIZATION_SAUVOLA:
+                thresh = mean.mul(1. + static_cast<float>(k) * (stddev / 128.0 - 1.));
+                break;
+            case BINARIZATION_WOLF:
+                minMaxIdx(src, &srcMin,NULL);
+                minMaxIdx(stddev, NULL, &stddevMax);
+                thresh = mean - static_cast<float>(k) * (mean - srcMin - stddev.mul(mean - srcMin) / stddevMax);
+                break;
+            case BINARIZATION_NICK:
+                sqrt(variance + sqmean, sqrtVarianceMeanSum);
+                thresh = mean + static_cast<float>(k) * sqrtVarianceMeanSum;
+                break;
+            default:
+                CV_Error( CV_StsBadArg, "Unknown binarization method" );
+                break;
+        }
+        thresh.convertTo(thresh, src.depth());
+
+        thresh.convertTo(test, src.depth());
+//
+//        cv::imshow("imagex",test);
+//        cv::waitKey(0);
+
+    }
+    // Prepare output image
+    _dst.create(src.size(), src.type());
+    Mat dst = _dst.getMat();
+    CV_Assert(src.data != dst.data);  // no inplace processing
+    // Apply thresholding: ( pixel > threshold ) ? foreground : background
+    Mat mask;
+    switch (type)
+    {
+        case THRESH_BINARY:      // dst = (src > thresh) ? maxval : 0
+        case THRESH_BINARY_INV:  // dst = (src > thresh) ? 0 : maxval
+            compare(src, thresh, mask, (type == THRESH_BINARY ? CMP_GT : CMP_LE));
+            dst.setTo(0);
+            dst.setTo(maxValue, mask);
+            break;
+        case THRESH_TRUNC:       // dst = (src > thresh) ? thresh : src
+            compare(src, thresh, mask, CMP_GT);
+            src.copyTo(dst);
+            thresh.copyTo(dst, mask);
+            break;
+        case THRESH_TOZERO:      // dst = (src > thresh) ? src : 0
+        case THRESH_TOZERO_INV:  // dst = (src > thresh) ? 0 : src
+            compare(src, thresh, mask, (type == THRESH_TOZERO ? CMP_GT : CMP_LE));
+            dst.setTo(0);
+            src.copyTo(dst, mask);
+            break;
+        default:
+            CV_Error( CV_StsBadArg, "Unknown threshold type" );
+            break;
+    }
+}
+
+#endif //SWIFTPR_NIBLACKTHRESHOLD_H