1 March 1991 Hybrid solution for high-speed target acquisition and identification systems
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A typical hierarchy for a general object recognition problem consists of object detection, classification and identification. Detection pinpoints the presence of an object or objects, classification categorizes the object(s), and identification distinguishes the object(s). This paper establishes necessary building blocks required for high-speed object recognition applications. An architecture that combines digital and optical processing, exploiting current image processing techniques for detection and classification, and optical processing hardware is described. An optical processing scheme is suggested for the identification aspect. Pre-processings that suppress background noise, minimize the number of matching filters and optimize post-processings of correlation outputs are performed by initially detecting objects in a background suppressed 2D scene via texture analysis and blob representation (detection), then scale/rotation estimation and shape recognition techniques (classification) are used as a precursor to optical processing. Post processing techniques which analyze and detect correlation peak(s) are also discussed. In addition, numerical results of each proposed concept are presented.
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gabriel Udomkesmalee, Gabriel Udomkesmalee, Marija Scholl, Marija Scholl, Michael S. Shumate, Michael S. Shumate, } "Hybrid solution for high-speed target acquisition and identification systems", Proc. SPIE 1468, Applications of Artificial Intelligence IX, (1 March 1991); doi: 10.1117/12.45451; https://doi.org/10.1117/12.45451


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