Scilab Image Processing


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Scilab Image Processing [SIP] is a tool for Image processing in Matlab written in C and Scilab. It is a complete and useful image toolbox that includes major tasks like edge detection, filtering, blurring, thresholding, histogram manipulation, segmentation, mathematical morphology, and color image processing. It contains several functions that have a flexible interface and error treatment. To know more about Scilab image processing, let’s know about its basics.

Major Features Of SIP

  • Provides unified binding for image processing libraries like ImageMagick, OpenCV, and also animal etc.
  • Used with GNU/Linux as its priority. Can work with Windows using SIVP and also IPD.
  • Provides rapid prototyping for imaging solution
  • Supports video processing beyond SIP.
  • Supports various data types and also data type conversions.
  • Provide specialized support for huge images.
  • Can work with Euclidean morphology related algorithms like dilation’s, distance transforms, watershed segmentation and also erosion.
  • Supports image type conversions like RGB to HSV, HSV to RGB, Indica to RGB
  • And so on

Another Important Toolbox Of Scilab Using Image Processing Is

SIVP (Scilab Image And Video Processing Toolbox)

  • Provides image processing and also video processing task
  • Supports 2D matrix and also images
  • Work with equal ease as with Matlab.
  • It needs the support of Scilab and also OpenCV
  • And so on


In Ubuntu Linux
  • SIVP through atoms(5.3 beta on-wards)
  • SIP through CVS
In Windows
  • SIVP through atoms(5.3 beta on-wards)
Image Processing Scilab Projects with source code

Basic Functions Of SIVP

  • Output=imwrite(input image, output image name)
  • Output image=imread(‘read image’)
  • Imshow(Output image)

Other Important Functions Are

  • Imdivide
  • im
  • imadd
  • imsubtract
  • imdivide
  • imabsdiff
  • mean2
  • std 2
  • imhist

Using Sci-lab In Image Processing, We Can Work On

  • Noise reduction
  • Image compression
  • High pass filtering and thresholding-edge detection
  • All types of filters
  • Advanced topics like FFT, Wavelet, Radon transform and Hough transform.

Major Applications Of Sci-Lab Using Image Processing Include

  • Quality control
  • In biotechnology for counting cells
  • In industries for the detection of surface defects
  • Detection of anatomical landmarks in the field of surgery
  • In the remote sensing, it is used for the classification of regions.

   We have provided a brief note about Scilab Image processing. Also, We have emphasized Scilab Image processing due to its current need and applications. Integrating Matlab and Scilab can give the best result while working with images. Knowing its advanced functionality, we are working on it for the past 7years. We have world-class certified developers working with us working on numerous projects using the concept of SIP. We are providing our service to all the students from all over the world. And up to now, we have provided more than 5000 projects and got the best feedback for our every work. Students can approach us anytime, as we are here only for you who feel to stand out.

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