private void btExtraction_Click(object sender, EventArgs e)
{
watch = new Stopwatch();
watch.Start();
feature = new double[countFile, 6];
int i = 0;
int j = 0;
foreach (var c in trainingData)
{
foreach (var fimage in c.Value)
{
glcm = new GLCMFeatureExtraction(new Clahe(8, 8, 256, 10, new Bitmap(fimage)).Process(), Convert.ToInt32(numGrayLevel.Value));
//glcm = new GLCMFeatureExtraction(new Bitmap(fimage), Convert.ToInt32(numGrayLevel.Value));
glcm.extract();
feature[j, 0] = glcm.getContrast();
feature[j, 1] = glcm.getDissimilarity();
feature[j, 2] = glcm.getEnergy();
feature[j, 3] = glcm.getEntropy();
feature[j, 4] = glcm.getHomogenity();
feature[j, 5] = i;
j++;
}
Console.WriteLine("Extraction Class : " + i + ", Now Time : " + watch.Elapsed.TotalSeconds + " s");
i++;
}
featureToTxt();
watch.Stop();
Console.WriteLine("Extraction Time : " + watch.Elapsed.TotalSeconds + " s");
btTraining.Enabled = true;
btAccuration.Enabled = true;
}
private int testingDataImage(Image img)
{
glcm = new GLCMFeatureExtraction(new Clahe(8, 8, 256, 10, new Bitmap(img)).Process(), Convert.ToInt16(numGrayLevel.Value));
//glcm = new GLCMFeatureExtraction(img, Convert.ToInt32(numGrayLevel.Value));
double[] testGlcm = new double[5];
glcm.extract();
testGlcm[0] = glcm.getContrast();
testGlcm[1] = glcm.getDissimilarity();
testGlcm[2] = glcm.getEnergy();
testGlcm[3] = glcm.getEntropy();
testGlcm[4] = glcm.getHomogenity();
return(lvq.testing(testGlcm, weightAkhir));
}
private void glcm(Image image)
{
progress.Maximum = 7;
progress.Value = 0;
GLCMFeatureExtraction glcm = new GLCMFeatureExtraction(image, 10);
progress.Value++;
glcm.extract();
progress.Value++;
log("Contrast : " + glcm.getContrast());
progress.Value++;
log("Disimiliarity : " + glcm.getDissimilarity());
progress.Value++;
log("Energy : " + glcm.getEnergy());
progress.Value++;
log("Entropy : " + glcm.getEntropy());
progress.Value++;
log("Homogenity : " + glcm.getHomogenity());
progress.Value++;
}
private void extractionTestingAccuration()
{
watch = new Stopwatch();
watch.Start();
int i = 0;
int correct = 0;
foreach (var c in testingData)
{
foreach (var fimage in c.Value)
{
bool corr = false;
var featureAccuration = new double[5];
glcm = new GLCMFeatureExtraction(new Clahe(8, 8, 256, 10, new Bitmap(fimage)).Process(), Convert.ToInt32(numGrayLevel.Value));
//glcm = new GLCMFeatureExtraction(new Bitmap(fimage), Convert.ToInt32(numGrayLevel.Value));
glcm.extract();
featureAccuration[0] = glcm.getContrast();
featureAccuration[1] = glcm.getDissimilarity();
featureAccuration[2] = glcm.getEnergy();
featureAccuration[3] = glcm.getEntropy();
featureAccuration[4] = glcm.getHomogenity();
int r = lvq.testing(featureAccuration, weightAkhir);
if (r == i)
{
correct++;
corr = true;
}
Console.WriteLine("Accuration File : " + fimage + ", Acc = " + corr + ", result = Class-" + r + ", Now Time : " + watch.Elapsed.TotalSeconds + " s");
}
i++;
}
double accurate = ((double)correct / (double)countFileTesting) * 100;
rcAccuration.Text = accurate + " %";
rcAccuration.SelectionAlignment = HorizontalAlignment.Center;
watch.Stop();
Console.WriteLine("Time Elapsed : " + watch.Elapsed.TotalSeconds + " s");
}