Bongard Pattern Recognition

Pattern recognition is a useful tool for mathematics, mathematical visualization, and art. After a brief description of Bongard’s methodology in the field of pattern recognition, the author introduces the concept of colour modularity and evaluates how it affects pattern recognition classification. Combining Bongard's methodology and colour modularity, the author attains a richer, more persuasive dynamic in pattern description and recognition of five- and ten-pointed star polygons.".
Keywords: pattern, pattern recognition, modularity, colour modularity, mathematics, mathematic visualization, deep learning, AI, pentagon, decagon, tessellation, M. Bongard, Bongard problem, Reza Sharhangi, Kharragan I,
Introduction
Marjorie Senechal wrote: ‘We encounter patterns all the time, every day, in the spoken word, in musical forms and video images in ornamental design and natural geometry’ [22]. Pattern recognition has been with us since the dawn of human consciousness noted Matson in Frontiers of Neuroscience: ‘Language mediated encoding and transfer of auditory and visual patterns is what enabled the rapid evolution of the human brain’ [15]. In recent history, this principle has become an engine of progress that affects all area of science, from mathematics to applied sciences, in areas like computer vision, signal analysis, speech comprehension, natural language analysis, and more recently machine learning and artificial intelligence.
This evaluation method to appraise and comprehend our physical reality has long fascinated me and I use regularly Russian physicist and
Its first step is relatively explicit, the following steps become gradually more adjustable, and the final build-up reaches a property that
Bongard calls ‘tentative’, insofar as the way a picture is represented is always tentative [2]. As cognitive Science professor Hofstadter summed up later, ‘Perception is pervaded by intelligence and intelligence by perception’