SCICBIR A CBIR system based on scilab

Content based image retrieval(CBIR) is an emerging area of research. Retrieving similar images from a given image has many applications in science engineering and medicine.
In scicbir  i have provided a basic CBIR system  in SCILAB.Please feel free to experiment with this system and develop further systems in SCILAB.
The source code is available at.
http://sourceforge.net/projects/sccilabcbir/

Cropping an Image in SCILAB

When cropping an image   , we  select a part of the image we  want and remove the rest.

You can crop an image using imcrop method in SIVP.

the format is imcrop(image,[x,y,width,height])

(x, y) is the top-left corner of the rectangle. Width and height are the width and height of the subimage.


Let us see what happens when we crops the image z below.

Example
z1=imcrop(z, [95, 20, 440,220]);

imshow(z1);
The result is:

Edge detection in SCILAB image processing

The SIVP toolbox provides for the common edge detection algorithms.The main methods provided are the frollowing. edge(im, method) edge(im, method, thresh) edge(im, method, thresh, direction) edge(im, method, thresh, sigma) [im1, thresh] = edge(im, method, ...) This works for gray scale images. Let us see an example.

z=imread('C:\Documents and Settings\Administrator\Desktop\Images\image06.jpg'); imshow(z); z1=rgb2gray(z); imshow(z1); E = edge(z1, 'sobel'); Also the canny edge detection method is supported. It is also to be noted that the SIP toolbox also supports edge detection like this.