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Bray, Brian K.

Publications and source records attributed to Bray, Brian K..

Description of SIS-AOP Result Format V1.0

Single Image SICD-Based Automatic Object Processing (SIS-AOP) is an automatic object identification tool for SAR imagery. It ingests a SAR image in standard SICD format, and it will run a suite of algorithms to cue possible vehicle detections, cull those detections and then ultimately label them either as detections only or possible expound to give a class-level ID or a vehicle-type ID. The SIS-AOP results are given in an XML (Extensible Markup Language) output format. This document defines the elements in the SISAOPR XML output format.

97 MATHEMATICS AND COMPUTING↗

SIS-AOP Cueing/Segmenting Algorithm (FOA_SIS-AOP) Using the Sandia FOA 4.0 Framework

For machine vision, one of the most important operations is fast and effective object cueing or segmentation. Sandia National Labs has a long history of development and implementation of very fast and effective cueing/segmentation algorithms. This report covers the history, motivation and implementation of evolving frameworks (Sandia FOA Frameworks) upon which this long legacy of successful algorithms are built. The report describes the innovative microprocessor implementation, enabling extremely fast morphological processing, combined with a novel adaptive quantization front - end and a feature - based backend that resulted in Sandia developing fast and effective cueing in a wide variety of applications, from defect detection to SAR ATR. The report covers evolution from Sandia FOA 1.0 Framework (1995) to current Sandia FOA 4.0 Framework (2021). Requirements for the cueing algorithm for SIS - AOP (FOA_SIS - AOP) that drove the Sandia FOA 4.0 Framework development are discussed, along with information on how to use the Sandia FOA Frameworks.

97 MATHEMATICS AND COMPUTING↗