private void match(string query, string template)
{
Change_Resolution(query);
Change_Resolution(template);
// Loading fingerprints
var fingerprintImg1 = ImageLoader.LoadImage(query);
var fingerprintImg2 = ImageLoader.LoadImage(template);
//// Building feature extractor and extracting features
var featExtractor = new PNFeatureExtractor()
{
MtiaExtractor = new Ratha1995MinutiaeExtractor()
};
var features1 = featExtractor.ExtractFeatures(fingerprintImg1);
var features2 = featExtractor.ExtractFeatures(fingerprintImg2);
// Building matcher and matching
var matcher = new PN();
double similarity = matcher.Match(features1, features2);
score = similarity.ToString("0.000");
MessageBox.Show(similarity.ToString("0.000"));
if (similarity >= 70)
{
MessageBox.Show("True");
}
else
{
MessageBox.Show("False");
}
}
private void match(string query, string template)
{
Change_Resolution(query);
Change_Resolution(template);
// Loading fingerprints
var fingerprintImg1 = ImageLoader.LoadImage(query);
var fingerprintImg2 = ImageLoader.LoadImage(template);
//// Building feature extractor and extracting features
var featExtractor = new PNFeatureExtractor()
{
MtiaExtractor = new Ratha1995MinutiaeExtractor()
};
var features1 = featExtractor.ExtractFeatures(fingerprintImg1);
var features2 = featExtractor.ExtractFeatures(fingerprintImg2);
// Building matcher and matching
var matcher = new PN();
double similarity = matcher.Match(features1, features2);
score = similarity.ToString("0.00");
string per = "percent";
label1.Text = similarity.ToString("0.00");
label3.Visible = true;
}
public result match(string query, string template)
{
Change_Resolution(query);
Change_Resolution(template);
// Loading fingerprints
var fingerprintImg1 = ImageLoader.LoadImage(query);
var fingerprintImg2 = ImageLoader.LoadImage(template);
//// Building feature extractor and extracting features
var featExtractor = new PNFeatureExtractor()
{
MtiaExtractor = new Ratha1995MinutiaeExtractor()
};
var features1 = featExtractor.ExtractFeatures(fingerprintImg1);
var features2 = featExtractor.ExtractFeatures(fingerprintImg2);
// Building matcher and matching
var matcher = new PN();
double similarity = matcher.Match(features1, features2);
score = similarity.ToString("0.00");
result.accuracy = score;
if (similarity > 75.0)
{
result.Code = 0;
result.Message = "Matched";
}
else
{
result.Code = 2;
result.Message = "Not Matched";
}
return(result);
}
private void match(string query, string template)
{
Change_Resolution(query);
Change_Resolution(template);
var fingerprintImg1 = ImageLoader.LoadImage(query);
var fingerprintImg2 = ImageLoader.LoadImage(template);
var featExtractor = new PNFeatureExtractor()
{
MtiaExtractor = new Ratha1995MinutiaeExtractor()
};
var features1 = featExtractor.ExtractFeatures(fingerprintImg1);
var features2 = featExtractor.ExtractFeatures(fingerprintImg2);
var matcher = new PN();
double similarity = matcher.Match(features1, features2);
score = similarity.ToString("0.000");
Console.WriteLine("the matched score is {0}", score);
if (similarity > 70)
{
MessageBox.Show("Its a Match !!", "Result", MessageBoxButtons.OK, MessageBoxIcon.Information, MessageBoxDefaultButton.Button1);
}
else
{
MessageBox.Show("Unsuccessfull !!", "Result", MessageBoxButtons.OK, MessageBoxIcon.Error, MessageBoxDefaultButton.Button1);
}
}
private void match(string query, string template)
{
Change_Resolution(query);
Change_Resolution(template);
var fingerprintImg1 = ImageLoader.LoadImage(query);
var fingerprintImg2 = ImageLoader.LoadImage(template);
var featExtractor = new PNFeatureExtractor()
{
MtiaExtractor = new Ratha1995MinutiaeExtractor()
};
var features1 = featExtractor.ExtractFeatures(fingerprintImg1);
var features2 = featExtractor.ExtractFeatures(fingerprintImg2);
var matcher = new PN();
double similarity = matcher.Match(features1, features2);
score = similarity.ToString("0.000");
MessageBox.Show("Similarity " + similarity.ToString("0.000"), "Results", MessageBoxButtons.OK, MessageBoxIcon.Information);
}
protected void Button6_Click(object sender, EventArgs e)
{
DataTable dv = db.selectquery("select * from voting where userid='" + id + "'");
if (dv.Rows.Count > 0)
{
// Label1.Visible = true;
Label1.Text = "already voted !!!";
}
else
{
try
{
string str1 = "figkk" + ".jpg";
Base64ToImage().Save(Server.MapPath("~/UploadTump/" + str1));
string Image1 = "~/UploadTump/" + str1.ToString();
string filePath1 = Server.MapPath(Image1);
string filename1 = Path.GetFileName(filePath1);
FileStream fs1 = new FileStream(filePath1, FileMode.Open, FileAccess.Read);
BinaryReader br1 = new BinaryReader(fs1);
bytes1 = br1.ReadBytes((Int32)fs1.Length);
DataTable dt = db.selectquery("select * from candidates where lid='" + id + "'");
string mm = dt.Rows[0]["fingerprint"].ToString();
vid = dt.Rows[0]["cid"].ToString();
string filePath = Server.MapPath(mm);
string filename = Path.GetFileName(filePath);
FileStream fs = new FileStream(filePath, FileMode.Open, FileAccess.Read);
BinaryReader br = new BinaryReader(fs);
bytes = br.ReadBytes((Int32)fs.Length);
var fingerprintImg1 = ImageLoader.LoadImage(filePath);
var fingerprintImg2 = ImageLoader.LoadImage(filePath1);
var featExtractor = new PNFeatureExtractor()
{
MtiaExtractor = new Ratha1995MinutiaeExtractor()
};
var features1 = featExtractor.ExtractFeatures(fingerprintImg1);
var features2 = featExtractor.ExtractFeatures(fingerprintImg2);
// Building matcher and matching
var matcher = new PN();
double similarity = matcher.Match(features1, features2);
score = similarity.ToString("0.000");
Label1.Text = similarity.ToString("0.000");
if (similarity > 40)
{
Label1.Text = " ";
DataList1.DataSource = db.selectquery("Select * from candidates where cid='" + vid + "'");
DataList1.DataBind();
Button2.Visible = true;
pnl_otp.Visible = true;
}
else
{
Label1.Text = "Invalid User !!!";
DataList1.DataSource = null;
DataList1.DataBind();
Button2.Visible = false;
}
}
catch (Exception ex)
{
// Label1.Visible = true;
Label1.Text = ex.Message.ToString();
}
}
}
