arXiv subjects

Prashanth Alluvada

Publications and source records attributed to Prashanth Alluvada.

3 recordsLinked to original sources

arXiv2013

Color Perception: Opening up the Chromaticity Cone

In the XYZ color space, the subset of the tri-stimuli corresponding to spike-type (monochromatic) impingement of energy is the chromaticity cone, CC. Using a family of concentric spheres, we describe a nonlinear transformation over the CC and construct a bijection from the CC onto the flat plane. In the process, we open up the CC and view it as a chart on the plane. Because the map is a bijection, the color perception information is preserved (invariant) through the transformation. We discuss stereographic projection of the chromaticity chart and some examples.

q-bio.QM↗

arXiv2008

Analytical Equations to the Chromaticity Cone: Algebraic Methods for Describing Color

We describe an affine transformation on the (CIE) color matching functions and map the spectral locus as a circle. We then homogenize the right circular cylinder erected by the circle, with respect to a normalizing plane and develop an analytical equation to the chromaticity cone, for the spectral colors. In the interior of the (CIE) chromaticity diagram, by homogenizing elliptic cylinders with respect to the normalizing planes, analytical equations to subsets (also cones) of the chromaticity cone are developed. These equations provide an algebraic method for describing color perception. As an application of the interior chromaticity cones, we demonstrate that by sectioning homogenized cones with planes and projecting, analytical equations to the Macadam ellipses may be derived. Further, the cone equations are used to propose new types of color order systems.

q-bio.OT↗

arXiv2008

Optimization Approach for Detecting the Critical Data on a Database

Through purposeful introduction of malicious transactions (tracking transactions) into randomly select nodes of a (database) graph, soiled and clean segments are identified. Soiled and clean measures corresponding those segments are then computed. These measures are used to repose the problem of critical database elements detection as an optimization problem over the graph. This method is universally applicable over a large class of graphs (including directed, weighted, disconnected, cyclic) that occur in several contexts of databases. A generalization argument is presented which extends the critical data problem to abstract settings.

cs.DB↗