Computer vision methods are proposed for feature extraction of structures of interest in schlieren images. The well studied curvature scale space is used to define features at physically salient points on shock contours. These points can include shock interactions, reflections, standoff distance, etc., and are present in many schlieren data. A challenge in developing methods for feature extraction in schlieren images is the reconciliation of existing techniques with structures of interest to an aerodynamicist. Domain-specific knowledge of physics must be incorporated into the definition and detection phases. Algorithms must be designed such that incorporation of an aerodynamic knowledge base is viable and known location and physically possible structure representations form a knowledge base that provides a unique feature definition and extraction. Model tip location and a shock intersection across several thousand frames in the complex double-cone schlieren sequence are identified, localized, and tracked. From examination of the sequence, the model appears still, and motion of the shock intersect is observed. Through the application of computer vision techniques, model stillness is confirmed, and the extent and pattern of the intersect motion are demonstrated.


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    Title :

    Detection, Localization, and Tracking of Shock Contour Salient Points in Schlieren Sequences


    Contributors:

    Published in:

    AIAA Journal ; 52 , 6 ; 1249-1264


    Publication date :

    2014-04-08


    Size :

    16 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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