並列探索による画像特徴抽出 : PAFEにおける並列オブジェクトによる探索

抄録

This paper introduces a new mechanism of PAFE which provides a flexible environment for feature extraction. This system is constructed based upon concurrent object model (multi agent model), in which many objects work co-operatively in concurrent ways. With these objects, this system performs the parallel search to extract the features from images. The features and their extraction methods are organized in a feature extraction network. In this network, features can be defined in multiple ways and can be extracted in multiple ways. Using this network, different paths (that means extraction method) can be executed in parallel. This system, therefore, provides a coarse grained parallelism which realizes the execution of multiple extraction methods for one kind of feature in parallel as well as extraction of multiple kinds of features in parallel. Also extraction combinations of top-down ways and bottom-up ways realize flexible control of the feature extraction. The efficiency was tested in some experiments in which this system was applied to some 2-dimensional objects.