Object pattern recognition below clutter in images

We are developing a technique for recognizing patterns below clutter based on modelling field theory. The presentation briefly summarizes the difficulties related to the combinatorial complexity of computations, and analyzes the fundamental limitations of existing algorithms such as multiple hypothesis testing. A new concept, dynamic logic, is introduced along with an algorithm suitable for pattern recognition in images with intense clutter data. This new mathematical technique is inspired by the analysis of biological systems, like the human brain, which combines conceptual understanding with emotional evaluation and overcomes the combinatorial complexity of model-based techniques. The presentation provides examples of object pattern recognition below clutter.