Use of Bi-Camera and Fusion of Pairwise Real Time Citrus Fruit Image for Classification Application

Use of Bi-Camera and Fusion of Pairwise Real Time Citrus Fruit Image for Classification Application

Peilin Li (University of South Australia, Australia), Sang-Heon Lee (University of South Australia, Australia) and Hung-Yao Hsu (University of South Australia, Australia)
DOI: 10.4018/978-1-4666-6030-4.ch004
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Abstract

In this chapter, the use of two images, the near infrared image and the color image, from a bi-camera machine vision system is investigated to improve the detection of the citrus fruits in the image. The application has covered the design of the bi-camera vision system to align two CCD cameras, the online acquisition of the citrus fruit tree image, and the fusion of two aligned images. In the system, two cameras have been registered with alignment to ensure the fusion of two images. A fusion method has been developed based on the Multiscale Decomposition Analysis (MSD) with a Discrete Wavelet Transform (DWT) application for the two dimensional signal. In the fusion process, two image quality issues have been addressed. One is the detail noise from the background, which is bounded with the envelope spectra and with similar spectra to orange citrus fruit and spatial variance property. The second is the enhancement of the fundamental envelope spectra using two source images. With level of MSD estimated, the noise is reduced by zeroing the high pass coefficients in DWT while the fundamental envelope spectra from the color image are enhanced by an arithmetic pixel level fusion rule. To evaluate the significant improvement of the image quality, some major classification methods are applied to compare the classified results from the fused image with the results from the types of color image. The misclassification error is measured by the empirical type errors using the manual segmentation reference image.

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