Papers by Lakshman Prasad
OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information), Jun 1, 2000
Image analysis is an important requirement of many artificial intelligence systems. Though great ... more Image analysis is an important requirement of many artificial intelligence systems. Though great effort has been devoted to inventing efficient algorithms for image analysis, there is still much work to be done. It is natural to turn to mammalian vision systems for guidance because they are the best known performers of visual tasks. The pulse-coupled neural network (PCNN) model of the cat visual cortex has proven to have interesting properties for image processing. This article describes the PCNN application to the processing of images of heterogeneous materials; specifically PCNN is applied to image denoising and image segmentation. Our results show that PCNNs do well at segmentation if we perform image smoothing prior to segmentation. We use PCNN for both smoothing and segmentation. Combining smoothing and segmentation enable us to eliminate PCNN sensitivity to the setting of the various PCNN parameters whose optimal selection can be difficult and can vary even for the same problem. This approach makes image processing based on PCNN more automatic in our application and also results in better segmentation.
This is the final report of the project titled, "Isotope Identification Algorithm for Rapid and A... more This is the final report of the project titled, "Isotope Identification Algorithm for Rapid and Accurate Determination of Radioisotopes," PMIS project number LA10-HUMANID-PD03. The goal of the work was to demonstrate principles of emulating a human analysis approach towards the data collected using radiation isotope identification devices (RIIDs). It summarizes work performed over the FY10 time period.
Springer eBooks, 2005
In an earlier work we proposed the chordal axis transform (CAT) as a more useful alternative to t... more In an earlier work we proposed the chordal axis transform (CAT) as a more useful alternative to the medial axis transform (MAT) for obtaining skeletons of discrete shapes. Since then, the CAT has benefited various applications in 2D and 3D shape analysis. In this paper, we revisit the CAT to address its deficiencies that are artifacts of the underlying constrained Delaunay triangulation (CDT). We introduce a valuation on the internal edges of a discrete shape's CDT based on a concept of approximate co-circularity. This valuation provides a basis for suppression of the role of certain edges in the construction of the CAT skeleton. The result is a rectified CAT skeleton that has smoother branches as well as branch points of varying degrees, unlike the original CAT skeleton whose branches exhibit oscillations in tapered sections of shapes and allows only degree-3 branch points. Additionally, the valuation leads to a new criterion for parsing shapes into visually salient parts that closely resemble the empirical decompositions of shapes by human subjects as recorded in experiments by M. Singh, G. Seyranian, and D. Hoffman.
ACM Transactions on Quantum Computing
As quantum computers become available to the general public, the need has arisen to train a cohor... more As quantum computers become available to the general public, the need has arisen to train a cohort of quantum programmers, many of whom have been developing classical computer programs for most of their careers. While currently available quantum computers have less than 100 qubits, quantum computing hardware is widely expected to grow in terms of qubit count, quality, and connectivity. This review aims at explaining the principles of quantum programming, which are quite different from classical programming, with straightforward algebra that makes understanding of the underlying fascinating quantum mechanical principles optional. We give an introduction to quantum computing algorithms and their implementation on real quantum hardware. We survey 20 different quantum algorithms, attempting to describe each in a succinct and self-contained fashion. We show how these algorithms can be implemented on IBM’s quantum computer, and in each case, we discuss the results of the implementation wi...
As part of the Thinking Telescopes project, a long-term Space Situational Awareness effort at the... more As part of the Thinking Telescopes project, a long-term Space Situational Awareness effort at the Los Alamos National Laboratory, we developed efficient algorithms for detecting and localizing unresolved moving sources in wide-field astronomical images. Our approach is based on pixel-by-pixel differencing of two images after one image has been convolved to match the point spread function of the other. The input images are obtained with the telescope tracking at the sidereal rate, and therefore stars are imaged as point sources and moving objects streak. The algorithm first identifies islands of connected pixels above a significance threshold in difference images where static sources have been removed. The next step is line detection and fitting light profiles of streaked sources using empirical models. The main objective is to optimize the accuracy of the measured streak end points while keeping the required computation reasonably fast. To this end we apply a series of progressively...
It is our hope that the Benchmark Imagery Suite will be useful to algorithm developers and that u... more It is our hope that the Benchmark Imagery Suite will be useful to algorithm developers and that users improve it so that it becomes a standard tool for testing and evaluating software to interpret overhead images of industrial facilities. Users with questions or comments are encouraged to contact either of the principal investigators. We welcome your remarks.
How can we synthesize edge information into meaningful objects?! ENTER: Delaunay triangulation; M... more How can we synthesize edge information into meaningful objects?! ENTER: Delaunay triangulation; Mother of all proximity graphs Defn: A triangulation of a point set where the interior of the circumcircle of each triangle is empty! Other properties:!
AD-A 243 256 ; t J L IU % JI C L A General Computational Framework for Distributed Sensing and Fault-Tolerant Sensor Integration
The design of Distributed Sensor Networks has to take into consideration sensor failures that occ... more The design of Distributed Sensor Networks has to take into consideration sensor failures that occur while functioning in the real (physical) world. This demands a technique of integration of sensor information that is faulttolerant so that the network is reliable for target recognition and tracking problems. (-I. In our earlier papertHL-_e- proposed a computational characterization of fault-tolerant integration of abstract sensors that were 1-interval estimates.....-h this paper,.we ' propose an abstract framework to address the general problem of fault-tolerant integration of sensor information in a general distributed sensor network. The essential ideas of this abstract framework stem from certain rudimentary notions in the theory of differentiable manifolds. This framework addresses a very general distributed sensor network both at the local level of sensor data integration at distributed processors as well as global exchange and assimilation of information available at various processors in the network. This paper is a continuation of our earlier work [LIKMI.
IEEE Parallel & Distributed Technology: Systems & Applications
A geometric transform for shape feature extraction
Spie Proceedings Series, 2000
... This enables the localization, extraction, and characterization of the morphological features... more ... This enables the localization, extraction, and characterization of the morphological features of shapes ... to characterize and represent a shape in terms of its morphological features is ... from its affine description to an invariant, and semantically salient feature-based representation in ...
Proceedings of the 14th International Conference on Image Analysis and Processing, Sep 10, 2007
We describe a new decomposition algorithm for twodimensional, polygonal shapes. The algorithm fir... more We describe a new decomposition algorithm for twodimensional, polygonal shapes. The algorithm first finds a set of overlapping ribbon-like subshapes ("ribbons") by grouping skeleton fragments into long smooth spines. The parts are then obtained by cutting the ribbons along lines of mutual intersection. With this approach we find part cuts that obey heuristic rules of early vision [17] without using boundary curvature.
System and method for the detection of anomalies in an image
Multiscale characterization and analysis of shapes
Semantic segmentation of multispectral overhead imagery
Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2016, 2016
A new image representation for compact and secure communication
Image segmentation by hierarchial agglomeration of polygons using ecological statistics
Advances in Distributed Sensor Integration: Application And Theory
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Papers by Lakshman Prasad