Folder Description

There are many basic algorithms of computer vision which are either implemented in MATLAB or Python-OpenCV. They can be downloaded or consulted for understanding. Few of the algorithms developed was a part of EE5731 visual computing course (National University of Singapore) requirement fullfillment.

MATLAB Folders:Denoted By PARTX

The folder can be saved to any directory.
There are six partx_xx folders.

Steps to Run the each part - a. Go to each part and extract vlfeat-0.9.21.rar folder. This folder contains the code for SIFT which has been downloaded from - https://www.vlfeat.org/overview/sift.html and is highly cited work.

b. First matlab working path should be the set to the part directory. For me to run the part1 code I need to set the working directory as -

E:\<Assignment_directory>\Assignment_1_Sayan_Kumar\Part1
Similarly to run the code for part2 change the MATLAB working directory to  
E:\<Assignment_directory>\Assignment_1_Sayan_Kumar\Part2

b. To run each part the following command to run -

 part1: 
 >> image= detect_edge("SOBEL","im01.jpg")
 >> image= detect_edge("GAUSIAN","im01.jpg",sigma,kernel_size) - Example : detect_edge("GAUSIAN","im01.jpg",1,3)
 >> image= detect_edge("HARR","im01.jpg",type,kernel_size) - Example 1:Unit Size Harr Feature Kernel of type 1- >> detect_edge("HARR","im01.jpg",1,1)
    Example 2: Harr Feature Kernel of type  of size 3- detect_edge("HARR","im01.jpg",5,3)
    %%% Unit Size Harr Kernel Types:
    %%% type 1 : (-1,+1) 
    %%% type2: tranpose(-1,+1)
    %%% type 3: (+1,-1,+1)
    %%% type 4: trnaspose(+1,-1,+1)
    %%% type 5: (-1,+1;+1,-1)
    %%% kernel_size will make the kernel bigger by kernel_size times.

 part2:
 >> [keypoints, descriptor]=sift_detector("im01.jpg")

 Part3:
 >> [H,image]=get_homography("h1.jpg","h2.jpg")  --> h1 to h2 homography
 >> [H,image]=get_homography("h2.jpg","h1.jpg")  --> h2 to h1 homography	

 Part4:
 >> [Hm,image]=get_homography_manual("im02.jpg","im01.jpg")  --> im02 to im01 homography and stitching

 Part5:
 >> [H12,image]=get_ransac_homography("im01.jpg","im02.jpg")  --> im01 to im02 automatic homography and stitching	
 >> [H21,image]=get_ransac_homography("im01.jpg","im02.jpg")  --> im01 to im02 automatic homography and stitching	

 Part6:
 >>[image]=get_basic_panorama("im01.jpg","im02.jpg","im03.jpg");

 NOTE: For Part7 to Part10. Download the GCMEX and Road Dataset( https://www.dropbox.com/s/rctkhpw6jh1p22o/Road.zip?dl=0) And add the path of the GCMEX and ROAD Appropriately as shown in the sample code in part1.m in Part7 folder
 part7: 
 >> part1

 part8:
 >> part2

 Part9:
 >> part3

 Part10:
 >> part4

Other Folder :

ORB_MATCHING: ORB Python-OPENCV Program has been implemented to match two images.

DATASET:

Dataset can be downloaded from : https://www.dropbox.com/s/rctkhpw6jh1p22o/Road.zip?dl=0

tatan432/Computer_Vision_Basics

Folder Description

MATLAB Folders:Denoted By PARTX

Other Folder :

DATASET: