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Image Processing and Computer Vision Toolbox

A Module of Image Processing and Computer Vision Toolbox for Scilab 6.0
(25692 downloads for this version - 250961 downloads for all versions)
Details
Version
1.1
A more recent valid version with binaries for Scilab 6.0 exists: 4.1.2
Author
Tan Chin Luh
Owner Organization
Trity Technologies
Maintainer
Chin Luh Tan
Category
License
Creation Date
April 5, 2017
Source created on
Scilab 6.0.x
Binaries available on
Scilab 6.0.x:
Linux 32-bit Linux 64-bit Windows 32-bit Windows 64-bit
Install command
--> atomsInstall("IPCV")
Description
            This module was previously based on SIVP module and now has been re-coded to
work with Scilab 6.0!

-------------------------------------------------------
Updated 6-Apr-17
-------------------------------------------------------
1. Add numbers of Feature Detection, Description and Matching functions. Example
at http://scilabipcv.tritytech.com/2017/04/05/image-matching/

2. Add object detection function

3. Add unit_tests

4. Add instructions at startup after installation for Linux Users.
-------------------------------------------------------
PLEASE SCROLL DOWN TO THE "NEWS" SECTION FOR THE INSTALLATION
INSTRUCTIONS ESPECIALLY FOR LINUX USER.
-------------------------------------------------------

Currently the module covers following areas:

IPCV - Image Processing and Computer Vision Toolbox for Scilab 

1. Analytic Geometry 
plot3dot — 3-D Parametric plot for points

2. Filter Design and Visualization 
fft2pad — Pad smaller matrix with zeros to the given size before
transformation. 
immesh — Visualize 2D matrix using mesh plot, useful for frequency response
visualization. 
imsmoothsurf — Visualize 2D matrix using smooth surf plot, useful for
frequency response visualization. 
imsurf — Visualize 2D matrix using surf plot, useful for frequency response
visualization. 
mkfftfilter — Create frequency domain filter 

3. Image Analysis and Statistics 
corr2 — 2D correlation coefficient 
edge — Find edges in a single channel image. 
imhist — get the histogram of an image 
impixel — Return selected pixel coordinates and values 
improfile — Return profiles for the selected 2 points 
mean2 — Average/mean of matrix elements 
std2 — Standard deviation of 2D matrix elements 
stdev2 — Standard deviation of 2D matrix elements 

4. Image Arithmetic 
imabsdiff — Calculate absolute difference of two images 
imadd — Add two images or add a constant to an image 
imcomplement — Complement image 
imdivide — Divide two images or divide an image by an constant. 
imlincomb — Linear combination of images 
immultiply — Multiply two images or multiply an image by an constant. 
imsubtract — Subtract two images or subtract a constant from an image 

5. Image Block Processing 
im2col — Convert image into series of columns 
imblockproc — Distict block processing for an image 
imblockslide — Sliding block processing for an image 
imcolproc — Sliding block processing for an image, with vectorization 

6. Image Enhancement and Restoration 
imadjust — Adjust the intensity of an image from given source histogram range
to the destination histogram range 
imdeconvl2 — Deconvolution with L2 Regularization 
imdeconvsobolev — Deconvolution by Sobolev Regularization 
imdeconvwiener — Deconvolution with Wiener method 
imdecorrstretch — Apply decorrelation stretch to multichannel image 
imhistequal — Histogram Equalization 
iminpaint — Restores the selected region in an image using the region
neighborhood 
immedian — Image median filter 
imnoise — Add noise (gaussian, etc.) to an image 
imwiener2 — Wiener filter for image 

7. Image Linear Filtering 
filter2 — 2D digital filtering 
fspecial — Create some 2D special filters 
imfilter — Image filtering 

8. Image Reading, Display and Exploration 
imdestroy — Destroy graphic window created using imdisplay (highgui). 
imdestroyall — Destroy ALL graphic window created using imdisplay (highgui). 
imdisplay — Display image using highgui for faster frame rate 
imread — Reads image file 
imshow — Display image in graphic window 
imwrite — Write image to file 
tifread — Special function to read 12-bits 1024x1024 CCD image 

9. Image Registration and Image Fusion 
imfuse — Image fusion 
imgettransform — Get transformation matrix from given source and destination
points 
imphasecorr — Detection and automatic image registration for translation,
rotation and scale using phase correlation method. 
imtransform — Image affine transformation 
warpmatselect — Selecting points for image transformation 

10. Image Transforms 
imdct — Discrete cosine transform (DCT) 
imhough — Image Hough transformation 
imhoughc — Image Hough transformation for Circle Detection 
imidct — Inverse discrete cosine transform (DCT) 
imlogpolar — Remaps an image to log-polar space. 
imradon — Calculates the 2D-Radon transform of the matrix 

11. Image Types and Color Space Conversions 
hsv2rgb — Convert a HSV image to the equivalent RGB image. 
im2bw — Convert image to binary 
im2double — Convert image to double precision 
im2int16 — Convert image to 16-bit signed integers 
im2int32 — Convert image to 32-bit signed integers 
im2int8 — Convert image to 8-bit signed integers 
im2uint16 — Convert image to 16-bit unsigned integers 
im2uint8 — Convert image to 8-bit unsigned integers 
imgraythresh — Calculate Otsu's Global threshold value 
imnorm — Normalize input 2-D Image to the range of 0-1 for double, or 0-255
for uint8 
mat2gray — Convert matrix to grayscale image 
ntsc2rgb — Convert a NTSC image to the equivalent RGB image. 
rgb2gray — Convert RGB images to gray images 
rgb2hsv — Convert a RGB image to the equivalent HSV image 
rgb2ind — Convert RGB image to index image 
rgb2lab — Convert from RGB color space to LAB color space 
rgb2ntsc — Convert a RGB image to the equivalent NTSC image YIQ. 
rgb2ycbcr — Convert a RGB image to the equivalent YCbCr image. 
xs2im — Convert graphics to an image matrix. 
ycbcr2rgb — Convert a YCbCr image to the equivalent RGB image. 

12. Morphological Operations 
bwborder — Find border for an image 
imblackhat — Image blackhat 
imblobprop — Calculate blobs properties from labeled image 
imclose — Image closing 
imcreatese — Creating Structure Element for Morphological operation 
imdilate — Image dilation 
imerode — Image erosion 
imgradient — Image gradient 
imhitmiss — Image Hit-Miss 
imlabel — Find blobs in an image 
imopen — Image opening 
imtophat — Image tophat 

13. Object Detection 
Coming soon


14. ROI Processing 
imroifill — Fill and image using the border color of the selected region 
imroifilt — Filtering of a selected region 

15. Spatial Transformations 
imcrop — Crop image 
imcropm — Crop an image using mouse selection 
impyramid — Image pyramid reduction and expansion 
imresize — Resizes image 
imrotate — Rotate an image to given angle 

16. Utilities and Interactive Tools 
im2movie — Create movie from sequence of images 
imaddtext — Adding text to a color image 
imbreakset — Set the break event with Scilab figure 
imbreakunset — Unset the break event with Scilab figure 
imcaminfo — Show the supported raw resolution for an USB camera (linux only) 
imdistline — Measure distance between 2 selected points in pixels. 
imlsusb — List all USB devices connected to PC (linux only) 
impixelval — Interactive tool to inspect pixel value at selected point 
imrects — Draw Bounding Boxes on An Image 
imroi — Select region of interest and create a mask from it 
imselect — Select points on an image. 
rectangle — Draw a rectangle on image 

17. Video Handling 
addframe — Add a frame to the video file. (experimental) 
aviclose — Close a video file. (experimental) 
avicloseall — Close all opened video files/cameras. (experimental) 
avifile — Create a new video file to write. (experimental) 
avilistopened — Show all opened video files. (experimental) 
aviopen — Open a video file. (experimental) 
avireadframe — Grabs and returns a frame from a opened video file or camera
(experimental) 
camopen — Open a camera. (experimental) 
camread — Grabs and returns a frame from a camera(experimental) 

18. Feature Detection, Description and Matching
imbestmatches — Find the best matched features from 2 features objects and the
matching matrix
imdetect_BRISK — Detect features from an image with BRISK algorithm
imdetect_DENSE — Detect features from an image with DENSE algorithm
imdetect_FAST — Detect features from an image with FAST algorithm. Usually
used for corner features.
imdetect_GFTT — Detect features from an image with GFTT algorithm
imdetect_HARRIS — Detect features from an image with HARRIS algorithm
imdetect_MSER — Detect features from an image with MSER algorithm
imdetect_ORB — Detect features from an image with ORB algorithm
imdetect_SIFT — Detect features from an image with SIFT algorithm
imdetect_STAR — Detect features from an image with STAR algorithm
imdetect_SURF — Detect features from an image with SURF algorithm
imdrawmatches — Draw matching result for 2 images
imextract_DescriptorBRIEF — Computes the descriptors for a set of keypoints
detected in an image with BRIEF method.
imextract_DescriptorBRISK — Computes the descriptors for a set of keypoints
detected in an image with BRISK method.
imextract_DescriptorFREAK — Computes the descriptors for a set of keypoints
detected in an image with FREAK method.
imextract_DescriptorORB — Computes the descriptors for a set of keypoints
detected in an image with ORB method.
imextract_DescriptorSIFT — Computes the descriptors for a set of keypoints
detected in an image with SIFT method.
imextract_DescriptorSURF — Computes the descriptors for a set of keypoints
detected in an image with SURF method.
immatch_BruteForce — Brute-force matcher for features matching.
plotfeature — Plot the features detected by feature detectors

            
Files (5)
[17.92 MB]
Linux 32-bit binary for Scilab 6.0.x

[19.68 MB]
Linux 64-bit binary for Scilab 6.0.x

[37.98 MB]
Source code archive

[24.58 MB]
Windows 32-bit binary for Scilab 6.0.x

[26.18 MB]
Windows 64-bit binary for Scilab 6.0.x

News (5)
Comments (3)     Leave a comment 
Comment from Alexander Jameson -- April 25, 2017, 07:42:30 PM    
This comment has been deleted.
Comment from Alexander Jameson -- May 15, 2017, 01:29:24 PM    
Nice to see macOS Sierra compatibility addressed with matplot etc. much obliged, thank you.
Comment from Clementeena AS -- January 9, 2020, 07:43:38 AM    
Hi,
 I am working on image processing, I am finding difficulty in detecting the objects in 
the given image.

Can you help me with highlighting the object in the original image after differentiating
the
the original image and the sample image.

thanks,
Teena
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