An introduction video on Scilab image processing

After so many years , I am coming back with a new post. Times have changed, Now there are some good videos on scilab image processing. Let me share one for you.

This is the first of a two part video secure series.Please feel free to comment.

We have to make Scilab stronger for image processing!!! So please contribute your EFFORT.

The need for advanced code in SCILAB for image processing applications is strongly felt. The only solution to this is community(students teachers and researchers) post their useful innovations as well as needs in SCILAB image processing  as comments.

Code examples are welcome Also request for specific applications are welcome and I hope that it will be addressed by community.

Also it will be nice if teachers guiding projects of students would take care to address the needs in this area and ask their students to do at least one project in developing a module for scilab. I would be very glad to give the links to scuch  projects and code in this blog.

Also innovative students can contribute a lot in this.

SCILAB is ours!! make it feature rich!!

SIVP on LINUX UBUNTU

Many people has reported problems in loading SIVP on ubuntu.

Please see the discussions in http://mailinglists.scilab.org/SIVP-amp-Ubuntu-td4025059.html

I feel we will have to wait till the error is fixed

If anybody have any suggestions regarding this error please comment.
regards
Kannan

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.

Converting RGB images to gray scale images.

RGB images can be converted into gray scale images in SCILAB by usibg RGB2gray x=imread('C:\Documents and Settings\Administrator\Desktop\Images\lena.jpg'); imshow(x).

z=RGB2Gray(x). imshow(z).