diff --git a/IRImageProcessing/Source.cpp b/IRImageProcessing/Source.cpp
index ff910b9..1e20275 100644
--- a/IRImageProcessing/Source.cpp
+++ b/IRImageProcessing/Source.cpp
@@ -2,6 +2,8 @@
 #include <bitset>
 #include <string>
 #include <filesystem>
+#include <fstream>
+#include <iostream>
 #include <vector>
 
 void thinningIteration(cv::Mat& img, int iteration) {
@@ -49,6 +51,7 @@
     } while (cv::countNonZero(diff) > 0);
     dst *= 255;
 }
+
 std::vector<cv::Point> findBranchPoints(cv::Mat& img)
 {
     std::vector<cv::Point> branchPoints;
@@ -96,18 +99,18 @@
                     int x = i + neighbor[0][k];
                     int y = j + neighbor[1][k];
 
-                    int nextX = i + neighbor[0][(k + 1) % 8];
-                    int nextY = j + neighbor[1][(k + 1) % 8];
+                    //int nextX = i + neighbor[0][(k + 1) % 8];
+                    //int nextY = j + neighbor[1][(k + 1) % 8];
 
                     if (thinnedImage.at<uchar>(x, y) == 255) {
                         neighborCount++;
 
-                        if (thinnedImage.at<uchar>(nextX, nextY) == 0)
-                            transitions++;
+                        //if (thinnedImage.at<uchar>(nextX, nextY) == 0)
+                        //    transitions++;
                     }
                 }
 
-                if (transitions == 1 && neighborCount == 3)
+                if (neighborCount >= 3)
                     bifurcationPoints.push_back(cv::Point(j, i));  // OpenCV�ł́Ax���W����ԍ��Ay���W���s�ԍ��ɑΉ����܂��B
             }
         }
@@ -122,13 +125,16 @@
     dst = src.clone();
     std::vector<std::vector<cv::Point>> contours;
     cv::findContours(src, contours, cv::RETR_EXTERNAL, cv::CHAIN_APPROX_SIMPLE);
+    std::ofstream outFile("area.txt");
     // �ʐς�臒l�ȉ��̗֊s���폜
     for (int i = 0; i < contours.size(); i++) {
         double area = cv::contourArea(contours[i]);
+        outFile << i << ": = " << area <<std::endl;
         if (area <= areaThreshold) {
             cv::drawContours(dst, contours, i, cv::Scalar(0), cv::FILLED);
         }
     }
+    outFile.close();
     return dst;
 }
 
@@ -150,26 +156,32 @@
 
 void BinaryProcessing(const cv::Mat& ori, const cv::Mat& src, std::string dirName)
 {
-    // ��Â̓�l��
-    cv::Mat otsuBinaryImage;
-    cv::threshold(src, otsuBinaryImage, 0, 255, cv::THRESH_BINARY_INV | cv::THRESH_OTSU);
-    // �K���I��l��
-    cv::Mat adaptiveBinaryImage;
-    cv::adaptiveThreshold(src, adaptiveBinaryImage, 255, cv::ADAPTIVE_THRESH_MEAN_C, cv::THRESH_BINARY_INV, 41, 10);
+    // ��l��
+    cv::Mat margeBinaryImage, removedMargeBinaryImage;
+    cv::threshold(src, margeBinaryImage, 55, 255, cv::THRESH_BINARY);
 
-    // �����t�H�W�[�ϊ��p�̃J�[�l��
-    cv::Mat element = cv::getStructuringElement(cv::MORPH_RECT, cv::Size(3, 3));
-    // �����t�H���W�[�ϊ�
+    // �p�f�B���O
+    int borderPixel = 30;
+    cv::Rect roi(borderPixel, borderPixel, margeBinaryImage.cols - borderPixel * 2, margeBinaryImage.rows - borderPixel * 2);
+    cv::Mat ROIImage;
+    ROIImage = margeBinaryImage(roi).clone();
+    cv::Mat paddingImage;
+    cv::copyMakeBorder(ROIImage, paddingImage, borderPixel, borderPixel, borderPixel, borderPixel, cv::BORDER_CONSTANT, cv::Scalar(0));
+
+    // �c��
     cv::Mat morphologyImage;
-    cv::morphologyEx(adaptiveBinaryImage, morphologyImage, cv::MORPH_OPEN, element);
-    
-    cv::Mat borderRemoved = morphologyImage(cv::Rect(10, 10, morphologyImage.cols - 20, morphologyImage.rows - 20));
-    cv::Mat borderAdded;
-    cv::copyMakeBorder(borderRemoved, borderAdded, 10, 10, 10, 10, cv::BORDER_CONSTANT, 255);
+    dilate(paddingImage, morphologyImage, cv::Mat::ones(5, 5, CV_8U), cv::Point(-1, -1), 2);
+
+
+    // ���̈�폜
+    cv::Mat removedMargeBinaryImage2;
+    double areaThreshold = 1000.0;
+    removedMargeBinaryImage = removeSmallAreaImage(morphologyImage, areaThreshold);
+
 
     cv::Mat invImage;
     cv::Mat thinnedImage;
-    thinning(morphologyImage, thinnedImage);
+    thinning(removedMargeBinaryImage, thinnedImage);
 
 
     cv::Mat kernel1 = cv::getStructuringElement(cv::MORPH_RECT, cv::Size(3, 3));
@@ -182,24 +194,33 @@
 
 
 
-    cv::bitwise_not(adaptiveBinaryImage, adaptiveBinaryImage);
-    cv::bitwise_not(morphologyImage, morphologyImage);
-    cv::bitwise_not(outputImage, outputImage);
-    cv::bitwise_not(thinnedImage, thinnedImage);
+    
+   /* morphologyImage = inverseImage(morphologyImage);
+    outputImage = inverseImage(outputImage);
+    thinnedImage = inverseImage(thinnedImage);*/
 
 
-    cv::imwrite(dirName + "/OtsuBinaryImage.png", otsuBinaryImage);
-    cv::imwrite(dirName + "/AdaptiveBinary.png", adaptiveBinaryImage);
+    /*cv::imwrite(dirName + "/OtsuBinaryImage.png", otsuBinaryImage);
+    cv::imwrite(dirName + "/AdaptiveBinary.png", adaptiveBinaryImage);*/
+    cv::imwrite(dirName + "/MargeTH60BinaryImage.png", margeBinaryImage);
+    cv::imwrite(dirName + "/RemovedSmallAreaMargeBinaryImage_" + std::to_string((int)areaThreshold) + ".png", removedMargeBinaryImage);
+
+    cv::imwrite(dirName + "/ROIImage.png", ROIImage);
+    cv::imwrite(dirName + "/paddingImage.png", paddingImage);
     cv::imwrite(dirName + "/Morpho.png", morphologyImage);
+
     cv::imwrite(dirName + "/Thinnig.png", thinnedImage);
     cv::imwrite(dirName + "/DilatedThinning.png", outputImage);
 
 
+
     cv::Mat circleImage;
     ori.convertTo(circleImage, CV_8U);
     cv::Mat circleImageRGB;
     cv::cvtColor(circleImage, circleImageRGB, cv::COLOR_GRAY2BGR);  // �O���[�X�P�[������RGB�֕ϊ�
 
+
+    
     std::vector<cv::Point> branchPoints = extractBifurcationPoints(thinnedImage);  // ����_�����o
 
     // ����_�ɉ~��`��
@@ -296,15 +317,12 @@
     double margeMinVal, margeMaxVal;
     cv::minMaxLoc(margeImage, &margeMinVal, &margeMaxVal); // �ŏ��l�ƍő�l���擾
     cv::normalize(margeImage, margeNormImage, 0, 255, cv::NORM_MINMAX, CV_8U);
-    cv::Mat margeBinaryImage, removedMargeOtsuBinaryImage;
-    cv::threshold(margeNormImage, margeBinaryImage, 60, 255, cv::THRESH_BINARY);
-    double areaThreshold = 1000.0;
-    removedMargeOtsuBinaryImage = removeSmallAreaImage(margeBinaryImage, areaThreshold);
-    cv::imwrite(dirName + "/MargeTH60BinaryImage.png", margeBinaryImage);
-    cv::imwrite(dirName + "/RemovedMargeSmallAreaBinaryImage_" +  std::to_string((int)areaThreshold) + ".png", removedMargeOtsuBinaryImage);
+    
+    //cv::imwrite(dirName + "/MargeOtsuBinaryImage.png", margeOtsuBinaryImage);
+    //cv::imwrite(dirName + "/RemovedSmallAreaMargeOtsuBinaryImage_" + std::to_string((int)areaThreshold) + ".png", removedMargeOtsuBinaryImage);
     cv::imwrite(dirName + "/Marge.png", margeImage);
     cv::imwrite(dirName + "/MargeNorm.png", margeNormImage);
-    //BinaryProcessing(ori, margeImage, dirName);
+    BinaryProcessing(ori, margeNormImage, dirName);
 
 }
 
@@ -313,11 +331,11 @@
 
 
 int main() {
-    std::string inputFileName = "experiment_0412_trimmed/hattori.tif";
+    std::string inputFileName = "trimmed.tif";
 
     // �o�͏���
-    std::string baseDir = "experiment_0412_result/";
-    std::string dirBaseName = "subject0_0_degree_";
+    std::string baseDir = "result_output/";
+    std::string dirBaseName = "th50_border30_kernel5_ite2_area1000";
     std::string dirName = baseDir + dirBaseName;
     
 
@@ -342,9 +360,7 @@
     cv::Mat windowedImage;
     WindowProcessing(image, windowedImage, 255.0, dirName);
 
-    // �m�C�Y����
-    cv::Mat gaussinaBlurImage;
-    cv::GaussianBlur(windowedImage, gaussinaBlurImage, cv::Size(3, 3), 9, 0);
+    
 
     // CLAHE��p�����q�X�g�O�������R��
     cv::Ptr<cv::CLAHE> clahe = cv::createCLAHE(10.0, cv::Size(16, 16));
@@ -356,9 +372,12 @@
     cv::threshold(claheImage, claheOtsuBinaryImage, 128, 255, cv::THRESH_BINARY);
 
     //BinaryProcessing(windowedImage, claheImage, dirName);
+    // �m�C�Y����
+    cv::Mat gaussianBlurImage;
+    cv::GaussianBlur(claheImage, gaussianBlurImage, cv::Size(19, 19), 9, 0);
 
     cv::Mat inversedClaheImage;
-    inversedClaheImage = inverseImage(claheImage);
+    inversedClaheImage = inverseImage(gaussianBlurImage);
 
     // �K�{�[���t�B���^
     GaborProcessing(windowedImage, inversedClaheImage, dirName);
@@ -367,9 +386,9 @@
 
     cv::imwrite(dirName + "/Original.tif", image);
     cv::imwrite(dirName + "/WindowedImage.png", windowedImage);
-    cv::imwrite(dirName + "/Gaussian.png", gaussinaBlurImage);
+    cv::imwrite(dirName + "/CLAHEGaussian.png", gaussianBlurImage);
     cv::imwrite(dirName + "/CLAHE.png", claheImage);
-    cv::imwrite(dirName + "/CLAHEInversion.png", inversedClaheImage);
+    cv::imwrite(dirName + "/CLAHEGaussianInversion.png", inversedClaheImage);
     cv::imwrite(dirName + "/CLAHEOtsu.png", claheOtsuBinaryImage);
 
     return 0;