A New Feedback-Based Method for Parameter Adaptation in Image Processing Routines.

ABSTRACT: The parametrization of automatic image processing routines is time-consuming if a lot of image processing parameters are involved. An expert can tune parameters sequentially to get desired results. This may not be productive for applications with difficult image analysis tasks, e.g. when high noise and shading levels in an image are present or images vary in their characteristics due to different acquisition conditions. Parameters are required to be tuned simultaneously. We propose a framework to improve standard image segmentation methods by using feedback-based automatic parameter adaptation. Moreover, we compare algorithms by implementing them in a feedforward fashion and then adapting their parameters. This comparison is proposed to be evaluated by a benchmark data set that contains ch

SUBMITTER: Khan AU 

PROVIDER: S-EPMC5072585 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature