Showing posts from August, 2016

Fuzzy Logic Image Processing

An edge is a boundary between two uniform regions. You can detect an edge by comparing the intensity of neighboring pixels. small intensity differences between two neighboring pixels do not always represent an edge. Instead, the intensity difference might represent a shading effect. The fuzzy logic approach for image processing allows you to use membership functions to define the degree to which a pixel belongs to an edge or a uniform region.
Import RGB Image and Convert to Grayscale
I = imread('peppers.png');
I' = 0.2989*I(:,:,1)+0.5870*I(:,:,2)+0.1140*I(:,:,3); figure; image(I','DataMapping','scaled'); colormap('gray'); title('Input Image in Grayscale') 

Convert Image to Double-Precision Data
I = double(I');
Type = class(I'); scaling = double(intmax(Type)); I = I/scaling; 

Obtain Image Gradient
Gx = [-1 1]; Gy = Gx'; Ix = conv2(I,Gx,'same'); Iy = conv2(I,Gy,'same'); figure; image(Ix,'DataMapping','s…

Top 10 Open Software for Image Processing Domain

OpenCV was designed for computational efficiency and with a strong focus on real-time applications.
VLFeat open source library implements popular computer vision algorithms specializing in image understanding and local features extraction and matching.

BoofCV is an open source Java library for real-time computer vision and robotics applications.