Mutation testing is a technique for unit-testing software that, although powerful, is
computationally expensive. The principal expense of mutation is that many variants of the …

For statistical design of an optimal filter, it is probabilistically advantageous to employ a large
number of observation random variables; however, estimation error increases with the …

Morphological image operators are a class of non-linear image mappings studied in
Mathematical Morphology. Many significant theoretical results regarding the characterization …

This paper proposes a computational modeling for image filtering processes based on the
Cartesian Genetic Programming (CGP) methodology, suitable for hardware devices. A …

A method has been developed to track a region related to respiration process in thermal
images. The respiration region of interest (ROI) consisted of the skin area around the tip of …

Representation of set operators by artificial neural networks and design of such operators by
inference of network parameters is a popular technique in binary image analysis. We …

A classical approach to designing binary image operators is Mathematical Morphology
(MM). We propose the Discrete Morphological Neural Networks (DMNN) for binary image …

This book addresses digital document enhancement and restoration in these settings.
Topics covered include the language and working definitions of the field, current industry …

In Machine Learning, feature selection is an important step in classifier design. It consists of
finding a subset of features that is optimum for a given cost function. One possibility to solve …

The design of binary morphological operators that are translation-invariant and locally
defined by a finite neighborhood window corresponds to the problem of designing Boolean …