US 8,428,348 B2 · Image analysis through neural network using image average color

Abstract

Architecture for comparing images by building an initial map from the average color and an inserted blackened area. Accordingly, a map can be built that is more information-rich and smaller, thereby making the system more efficient. The architecture employs a Kohonen neural network (or self-organizing map (SOM)) by guiding the learning of the SOM using characteristics of the images such as average color and a central area. A strong component of the average color of the image and the central area at the approximate center of the image are added to the uninitialized SOM, which allows related colors to converge toward the central area of the image. When input, the SOM organizes the color content of the image on a map, which can be used to compare the image with other images.

Claims20

Dependent claims

A computer-implemented image system, comprising:

an analysis component that builds a reduced in size vector map for analyzing image characteristics of an image, the vector map includes a perimeter region that is an average color value of the image;
a classification component for classifying the image relative to a second image based on classification information computed from the average color of the image;
and
a microprocessor that executes computer-executable instructions associated with at least one of analysis component or the classification component.

1 more element

Dependencies are inferred from the claim text.

Image analysis through neural network using image average color

Life of this patent

Image analysis through neural network using image average color

Life of this patent

Abstract

Claims20