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Fluorescent Uv Imaging System for Inspection of Defected Citrus Fruits

M. A. Momin
Department of Farm Power and Machinery, Bangladesh Agricultural University, Mymensingh-2202, Bangladesh

M. S. Sultana
Department of Farm Power and Machinery, Bangladesh Agricultural University, Mymensingh-2202, Bangladesh

M. H. Islam
Department of Farm Power and Machinery, Bangladesh Agricultural University, Mymensingh-2202, Bangladesh

T. Shiigi
Division of Environmental Science and Technology, Graduate School of Agriculture, Kyoto University, Sakyo-ku, Kyoto 606-8502, Japan

N. Kondo
Division of Environmental Science and Technology, Graduate School of Agriculture, Kyoto University, Sakyo-ku, Kyoto 606-8502, Japan

Abstract/ Executive Summary:

This research was carried out to develop a machine vision system under UV illumination which could identify the fluorescence area on defective especially rotten, damaged, or injured citrus surfaces. Since damaged citrus peel includes fluorescent substances, it was easy to discriminate fluorescence parts from healthy parts. The target objects whose surfaces were defected were acquired by a camera is VGA format using UV lamps (radiating black light wave-lengths). The results showed that the black lighting system is practically suitable in commercial applications and that the proposed algorithm of fluorescence area detection is effective and the processing speed is increased.

Keywords: Flurescent, Image, Citrus fruits

Location: Department of Farm Power and Machinery, Bangladesh Agricultural University, Mymensingh-2202,

Start Date: 00-11-2013

End Date: 00-04-2013

Program Area: Farm Mechanization

Commodity: Orange

Objectives:

1. The goal of this work was to develop an algorithm which could detect the fluorescent regions present on the defected surface of citrus, and 2. The first objective to achieve this goal is to develop the fluorescence imaging based machine vision system which can be work efficiently to acquire fluorescent image and then development an algorithm to identify fluorescent region.

Methodology:

Machine vision systems utilize imaging cameras ranging from monochrome cameras performing simple shape and size recognition tasks to common aperture multispectral cameras for detection of surface defects and diseases on meat, grains, fruits, and vegetable. Since fluorescent light from rotten or injured parts is a greenish color, it is considered that a color TV camera used for colour imaging can also be used for fluorescence imaging. Recent developments of microcomputer-based image processing system have boosted wider applications of machine vision technique in the post harvest food processing. VGA, XGA, SXGA, and UXGA format colour cameras with 8 or 10 bit gray levels are starting to be used. These cameras have the potential to detect the defective parts of citrus, by a new algorithm of high resolution fluorescence images which comes close to human eyes performance. The target objects whose surfaces are damaged or rotten were acquired by a VGA format camera (Sony ICX424AQ) of 8 bit gray levels. In UV-fluorescence imaging technique, sample surface illumination is done using UV light whereas the signal is detected in visible or infrared band. The sample absorbs UV light and then radiates energy at a longer wavelength. As mentioned earlier the fluorescent compounds in citrus peel emit fluorescence in the visible (VIS) region of the spectrum when excited with UV radiation. In this experiment, the fluorescence images were acquired using UV lamp (Black light blue lamp). Since the UV lamps emission intensity is not high enough hence the black lighting system composed of four fluorescent lamps (FL6BLB Sankyo Denki Company) emitted rays at 315-400?nm with the peak at 350 nm.

Source of Information: Journal of Agricultural Engineering, The Institution of Engineers, Bangladesh, Vol. 41/AE Number 1, June, 2014

Article Link (Online Journal):

Funding Source:

Total Budget (Tk.) :

Achievement/Findings:

Based on acquired images, it is observed that a black lighting system is suitable to recognize the rotten or injured areas on citrus and feasible for practical applications. An algorithm for detecting fluorescent area on the defective citrus peel using fluorescence imaging based machine vision system was developed. The proposed algorithm is simple and faster and which is able to detect the defected areas from sound surfaces by setting a simple thresholding.

Knowledge Management: Journal