maheshmc2

public class Gp4 {
  public static void main(String... args ){
    java.util.Scanner read = new java.util.Scanner(System.in);
    System.out.println("Number of Lines are: ");
    int no = read.nextInt();
    
    String[] input = new String[no];
    
    for(int i=0; i<no ; ){
   //   System.out.println("Enter for i = "+i);

maheshmc2

this.queryName = qname;

        JFrame frame = new JFrame(title);
        frame.setLayout(new GridLayout(2, 1)); //.. UPPER FOR QUERY AND LOWER FOR RESULT

        this.ijtable = new ImageJTable(result, Setting.getColumnCount());
        ijtable.setVisible(true);
        JScrollPane pane = new JScrollPane(ijtable);
        
        JLabel query = new JLabel(new ImageIcon(ImageResize.resize(queryName, Setting.getQueryWidth(), Setting.getQueryWidth())));

maheshmc2

import java.io.File;
import javax.swing.JFileChooser;
import javax.swing.JPanel;

public class TestFileChooser extends JPanel {

    public static void main(String... args){
        TestFileChooser tf = new TestFileChooser();
        tf.showMe();
        //  jf.showOpenDialog(TestFileChooser.this);

maheshmc2

function F = getTexture(image)

output_bits=1;
input_bits=8;
theta=45;
d=205;


% getting the size of the input image

maheshmc2

Create table employee (
id Number,
name Varchar(20),
Primary Key(id)
)

maheshmc2

CREATE TYPE Texture AS OBJECT(
    entropy NUMBER(10,10),
    energy NUMBER(10,10),
    inertia NUMBER(10,10),
    inverseDiffMoment NUMBER(10,10),
    correlation NUMBER(10,10),
    infoCorrelation1 NUMBER(10,10),
    infoCorrelation2 NUMBER(10,10),
    sumAvg NUMBER(10,10),
    sumVar NUMBER(10,10),

maheshmc2

function [Similarity] = HSVcomp(Hist1, Hist2)

range = 0.0:0.1:1.0;
rangeNew = 0.0:0.05:1.0;
[x,y,z]    = meshgrid(range);
[x2,y2,z2] = meshgrid(rangeNew);

% decision thresholds:
t = 0.010;
t2 = 0.8;

maheshmc2

function [Similarity] = HSVcomp(Hist1, Hist2)

range = 0.0:0.1:1.0;
rangeNew = 0.0:0.05:1.0;
[x,y,z]    = meshgrid(range);
[x2,y2,z2] = meshgrid(rangeNew);

% decision thresholds:
t = 0.010;
t2 = 0.8;

maheshmc2

clc;
clear all;

Hist1 = getHSVHistogram('C:\Documents and Settings\All Users\Documents\My Pictures\Sample Pictures\Winter.jpg');
Hist2 = getHSVHistogram('C:\Documents and Settings\All Users\Documents\My Pictures\Sample Pictures\Water lilies.jpg');

% decision thresholds:
t = 0.010;
t2 = 0.8;

maheshmc2

function [Centroid, Area, Eccentricity, Perimeter, shape_histogram] = DAC(imgname)

%% Basic Processing

I = imgname;
I = rgb2gray(I);

threshold = graythresh(I);
BW = im2bw(I, threshold);
BW = ~BW;