A Spatial Filter for Dark Regions Detection

This paper presents a new spatial filter for detection of dark objects in images with uneven illumination or where object grey-levels vary with respect to local surroundings. Theoretical filter foundations, properties and guidelines for its application are described in detail. This parametric, symmetric, and rotation invariant filter adapts by varying its radius, and, consequently, enables scale-space image analyzing. Filter executes very fast also by big radii, because majority of filter mask elements are zero. Preliminary results are very promising. Proposed filter outperforms related methods like thresholding and local standard deviation in specific images, and, therefore, it is efficient supplement for these methods. With two integrated post-processing methods, this filter successfully deals also with image noise. Consequently, introduced filter can be legitimate reckoned among basic low-level digital image processing tools