A grayscale hit-or-miss transform based on level sets

The hit-or-miss transform (HMT) is a powerful morphological tool for the processing of binary images. There have been several attempts to generalize it to grayscale images, based on the grayscale erosion. The goal is to obtain a translation invariant recognition tool, with some robustness regarding small deformations and variations of illumination. We propose a definition of the hit-or-miss transform based on level sets. We call it the level set hit-or-miss transform (LSHMT). We compare its performance with that of another grayscale HMT found in the literature. The task performed is that of face localization on grayscale images, based on a set of face patterns. The empirical results on a database show the greater robustness of the LSHMT. The generalization of LSHMT using connected and morphological operators by reconstruction are proposed as feasible lines of research to increase its robustness. We are also working in its generalization to color images and image sequences.