{'fraction_non_alphanumeric': 0.018628912071535022, 'fraction_numerical': 0.0, 'mean_word_length': 6.1436170212765955, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A holistic and adaptive approach for automated prototyping of image processing functionality

Image Processing is fundamental for any camerabased vision system. In order to automate the prototyping process of image processing solutions to some extend, we propose a holistic, adaptive approach that comprises concepts for specification, composition, recommendation, execution, and rating of image processing functionality. The fundamental idea is to realize image processing applications according to Service-oriented Computing design principles. That is, distinct image processing functionality is encapsulated in terms of stateless services. Services are then used as building blocks for more complex image processing functionality. To automatically compose complex image processing functionality, our proposed approach incorporates a flexible, Artificial Intelligence planning-based forward search algorithm. Decision-making between alternative composition steps is supported by a learning recommendation system, which keeps track of valid composition steps by automatically constructing a composition grammar. In addition, it adapts to solutions of high quality by means of feedback-based Reinforcement Learning techniques. A concrete use case serves as proof of concept and demonstrates the feasibility of our holistic, adaptive approach.