Object detection in color images using nonparametric Bayes classification and orthogonal functions

Mehmet Celenk; Yuan Shao

doi:10.1117/12.316403

6 July 1998 Object detection in color images using nonparametric Bayes classification and orthogonal functions

Mehmet Celenk, Yuan Shao

Proceedings Volume 3387, Visual Information Processing VII; (1998) https://doi.org/10.1117/12.316403
Event: Aerospace/Defense Sensing and Controls, 1998, Orlando, FL, United States

Abstract

In this paper, we present a supervised, nonparametric Bayesian approach to object detection problem in color images. The proposed method does not assume any a priori knowledge about the object color distributions and their forms. It estimates the underlying color densities directly from the given image data. In this respect, the algorithm is not affected by substantial variations in the input scenes. For density estimation, the object color distributions are expanded in a series of orthogonal basis functions in the (R,G,B)-color space. The basis functions selected are the Hermite polynomials since their region of orthogonality spans the entire red, green, and blue coordinate axes. Several color images of complex shaped objects are processed by the detection method in the computer simulation. The input images are varied in size to determine the computational cost of the algorithm. During the training phase, the object and background color densities of the selected images are estimated using the first seventeen Hermite polynomials. In the classification phase, the nonparametric Bayesian classifier is applied to the input images to detect the objects of interest. Even for noisy images of textured scenes, the algorithm has detected the regions of interest with high accuracy. The experimental results indicate that the seventeen lowest-order Hermite polynomials are sufficient for accurate color density estimation. The computational cost of the method is also reasonably low for this type of iterative density estimation process.

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Mehmet Celenk and Yuan Shao "Object detection in color images using nonparametric Bayes classification and orthogonal functions", Proc. SPIE 3387, Visual Information Processing VII, (6 July 1998); https://doi.org/10.1117/12.316403

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KEYWORDS

Image processing

Image classification

Color image processing

Computer simulations

Binary data

Image analysis

Information visualization

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