Almost Uniform Distributions for Computer Image Enhancement
IEEE Transactions on Computers
A Numerical Algorithm for Identifying Spread Functions of Shift-Invariant Imaging Systems
IEEE Transactions on Computers
Texture Measures for Automatic Classification of Pulmonary Disease
IEEE Transactions on Computers
Extraction of Connected Edges from Knee Radiographs
IEEE Transactions on Computers
An Algorithm for Grey-Level Transformations in Digitized Images
IEEE Transactions on Computers
The description of scenes over time and space
AFIPS '73 Proceedings of the June 4-8, 1973, national computer conference and exposition
Expert Systems with Applications: An International Journal
MRI texture analysis in multiple sclerosis
Journal of Biomedical Imaging - Special issue on MRI in Neurosciences
| Hi-index | 15.00 |
Feature extraction is one of the more difficult steps in image pattern recognition. Some sources of difficulty are the presence of irrelevant information and the relativity of a feature set to a particular application. Several preprocessing techniques for enhancing selected features and removing irrelevant data are described and compared. The techniques include gray level distribution linearization, digital spatial filtering, contrast enhancement, and image subtraction. Also, several feature extraction techniques are illustrated. The techniques are divided into spatial and Fourier domain operations. The spatial domain operations of directional signatures and contour tracing are first described. Then, the Fourier domain techniques of frequency signatures and template matching are illustrated. Finally, a practical image pattern recognition problem is solved using some of the described techniques.