Program to perform simple image manipulation like smoothing, rotating, downsampling, detecting edges (x derivative, y derivative and magnitude of gradients), and plotting the gradient vectors.
It is a program to perform simple image manipulation with following requirements:
Load an image by reading it from a file or capturing it directly.
Image should be read as a 3 channel color image.
Program should work on any size of image.
On pressing a support key, apply corresponding function on the original image.
When implementing convolution, use Cython to speed up execution.
Program was implemented using Python, Cython, and OpenCV. Refer the report for further implementation details and instructions to run the code:
View Report
List of Support Keys:
i - Reload the original image (cancel any previous processing).
w - Save the current image into the file 'out.jpg'.
g - Convert the image to grayscale using the openCV conversion function.
G - Convert the image to grayscale using implemented conversion function.
c - Cycle through the color channels of the image showing a different channel every time the key is pressed.
s - Convert the image to grayscale and smooth it using the openCV function. Use track bar to control the amount of smoothing.
S - Convert the image to grayscale and smooth it using implemented function which should perform convolution with a suitable filter. Use track bar to control the amount of smoothing. Convolution function is implemented from scratch using Cython.
d - Downsample the image by a factor of 2 without smoothing.
D - Downsample the image by a factor of 2 with smoothing.
x - Convert the image to grayscale and perform convolution with an x derivative filter. Normalize the obtained values to the range [0,255].
y - Convert the image to grayscale and perform convolution with a y derivative filter. Normalize the obtained values to the range [0,255].
m - Show the magnitude of the gradient normalized to the range [0,255]. The gradient is computed based on the x and y derivative of the image.
p - Convert the image to grayscale and plot the gradient vectors of the image every N pixels. Length of vector is a fixed value K. Use track bar to control N.
r - Convert the image to grayscale and rotate it using an angle of theta degrees. Use track bar to control theta.
h - Display support keys
Results
Grayscale image with OpenCV and conversion function:
OpenCV
Conversion Filter
Cycle through color channels of the image:
Red Channel
Green Channel
Blue Channel
Smoothing image with OpenCV and convolution function:
OpenCV
Cython Function
Downsampling with and without smoothing:
Downsampling without smoothing
Downsampling with smoothing
X & Y derivative and Magnitude of gradient:
X derivative
Y derivative
Magnitude of gradient
Plot gradient vectors of image every N pixels:
Plotted gradient vectors at every 50 pixels
Roatation of image:
Rotated image at 45 degrees
About
Program to perform simple image manipulation like smoothing, rotating, downsampling, detecting edges (x derivative, y derivative and magnitude of gradients), and plotting the gradient vectors.
