The US Army Joint Service Agent Water Monitor (JSAWM) program is currently interested in an approach that can implement a hardware- designed device in ticket-based hand-held assay (currently being developed) used for chemical/biological agent detection. This paper presents a preliminary investigation of the proof of concept. Three components are envisioned to accomplish the task. One is the ticket development which has been undertaken by the ANP, Inc. Another component is the software development which has been carried out by the Remote Sensing Signal and Image Processing Laboratory (RSSIPL) at the University of Maryland, Baltimore County (UMBC). A third component is an embedded system development which can be used to drive the UMBC-developed software to analyze the ANP-developed HHA tickets on a small pocket-size device like a PDA. The main focus of this paper is to investigate the third component that is viable and is yet to be explored. In order to facilitate to prove the concept, a flatbed scanner is used to replace a ticket reader to serve as an input device. The Stargate processor board is used as the embedded System with Embedded Linux installed. It is connected to an input device such as scanner as well as output devices such as LCD display or laptop etc. It executes the C-Coded processing program developed for this embedded system and outputs its findings on a display device. The embedded system to be developed and investigated in this paper is the core of a future hardware device. Several issues arising in such an embedded system will be addressed. Finally, the proof-of-concept pilot embedded system will be demonstrated.
There is an immediate need for the ability to detect, identify and quantify chemical and biological agents in water supplies during water point selection, production, storage, and distribution to consumers. Through a U.S. Army sponsored Joint Service Agent Water Monitor (JSAWM) program, based on hand-held assays that exist in a ticket format, we are developing new algorithms for automatic processing of tickets. In previous work, detection of control dots in the tickets was carried out by traditional image segmentation approaches such as Otsu's method and other entropy-based thresholding techniques. In experiments, it was found that the approaches above were sensitive to illumination effects in the camera reader. As a result, more robust, object-oriented approaches to detect the control dots are required. Mathematical morphology is a powerful technique for image analysis that focuses on the size and shape of the objects in the scene. In this work, we describe a novel application of morphological operations in identification of control dots in hand held assay ticket imagery. Such images were pre-processed by a light compensation algorithm prior to morphological analysis. The performance of the proposed approach is evaluated using Receiving Operating Characteristics (ROC) analysis.
KEYWORDS: Target detection, Signal to noise ratio, Optical filters, Error analysis, Linear filtering, Signal processing, Electronic filtering, Hyperspectral target detection, Signal detection, Filtering (signal processing)
The Orthogonal Subspace Projection (OSP) and Constrained Energy Minimization (CEM) have been used in hyperpsectral target detection and classification. A target-constrained interference-minimized filter (TCIMF) was recently proposed to extend the CEM to improve signal detectability to annihilating undesired target signal sources as the way carried out in the OSP. In this paper, we revisit the TCIMF from a signal processing viewpoint where signals can be characterized by three types of information sources, desired target sources and undesired target sources, both of which are provided a priori, and interferers which are unknown interfering sources. By virtue of such signal decomposition, we chan show that the TCIMF is actually a generalization of the OSP and CEM. In particular, we investigate assumptions made for the OSP and CEM in terms of these three types of signal sources and exploit insights into their filter design. As will be shown in this paper, the OSP and the CEM perform the same tasks by operating different levels of information and both can be viewed as special cases of the TCIMF.