Post on 26-Dec-2015
transcript
Parallel Edge Detection
Daniel DobkinAsaf Nitzan
Introduction to Image Processing What are edges? Why do we need to find
them? How do we find them? Motivation to parallelize this process OpenMP implementation
We’ll talk about…
2-D / 3-D array of pixels Color channels
RGB – 3 channels Grayscale – 1 channel
1 byte per channel values of 0-255
What is an image?
A closer look at pixels
R = 225G = 157B = 168
R = 201G = 120B = 137
Edges
A sharp change in values of adjacent pixels
Motivation to find edges A very basic feature in image
processing
First, convert image from RGB to Grayscale
Convolve the image with a special 2-D operator
A greater change in intensity indicates a more prominent edge
Sobel operator:
Finding Edges
217
221
44
213
13 2
24 3 2
Finding Edges - Example
For Sobel x filter: -617 For Sobel y filter: -669
So now we have 2 numbers, now what? We calculate the magnitude and the orientation of the
gradient:
Large amount of computations 800 x 600 pixels = 480,000 pixels 5.5 million
additions, 2 million multiplications Especially when it comes to real-time
video… 24 fps = 11.5 million pixels 132 million
additions, 48 million multiplications…
Motivation to Parallelize
Processors access same shared memory Each processor performs the region of image
assigned to him Reduced communication - There is no need to
broadcast the pixels of the image to all other processors
openMP
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B
C
D
openMP Implementation
A
B
C
D
Master thread
Master thread
Parallel task – Sobel filtering
fork join
Multithreading Master thread forks a number of threads which
execute code in parallel
Original Image
Load Image from Main memoryAllocate memory to new imageSet number of threads#pragma omp parallel for \
shared(inputImage, outputImage, width, height)\private(StartPixel, NumOfThreads, Rank , xPixel, yPixel)for each Pixel in region
Convert RGB value to greyscaleCompute gradient using Sobel filter Store result in filtered image
Join all threadsStore new image to disk
Pseudocode
openMP Implementation
A
B
C
D
Original ImageProcessor 1
Processor 2
Processor 3
Processor 4
Sobel
Sobel
Sobel
Sobel
A
B
C
D
Filtered Image
Main Memory
Speedup Graph
Linear Speedup due to low communication cost
http://www.cs.rit.edu/~ptt/courses/4003-531/