棉 花 学 报    Cotton Science   2006，18(5)：299-303

Probe on the Morphology-Based Auto-Segmentation Technique for the Preharvest Cotton Images photoed on the Dark Background
WANG Ling¹，JI Chang-ying^1*，CHEN Bing-lin²
(1.Engineering College，Nanjing Agricultural University，Nanjing 210031，China；2. Key Laboratory of Crop Regulation，Ministry of Agriculture，Nanjing Agricultural University，Nanjing 210095，China)

Abstract：In this experiment，63 sheets of photos，viz. 7 grades and 9 sheets per grade，of the preharvest cotton image with natural shape photoed on the dark background afield were selected as samplings. The cotton binary template with bracteoles can be extracted by the followed steps：⑴ The original gray image was transformed to the binary image with the min-threshold in the left side of trough span of its histogram，and the center binary template can be extracted，which may lose some bracteoles in the border of cotton. ⑵ By dint of tophat cutting preprocess，the bracteoles in the border of cotton became more bright. The enhanced gray image was transformed to the binary image with the Otsu's threshold，and the periphery binary template can be extracted. ⑶ The center binary template plus periphery binary template is the preharvest cotton binary template with bracteoles namely. The experimental result indicates that the preharvest cotton binary template with bracteoles reached high precision，viz.98.4%.
    The segmentation arithmetic between cotton and its bracteoles consists of three aspects followed ：⑴ As a result of the bothat preprocessing，the intensity troughs between cotton petals was found and the periphery bracteoles region showed a granule appearance using a small structuring element. The enhanced gray image was transformed to the binary image with the Otsu's threshold，and the area of every bracteole is far smaller than the area of each cotton petal，which is the key technology in this experiment. ⑵ By dint of opening operation using a big self-adaptive structuring element，the connectivity statistics of the cotton image，viz.the number of objects，can be obtained in the opened binary image to judge the grade of preharvest cotton. ⑶ To the lower grade of preharvest cotton with multiple-connectivty，cotton petals not exceeding four was extracted from the non-opened binary image in turn according to the above-mentioned key technology. To the higher grade of preharvest cotton with single-connectivity，the original gray image was transformed to the binary image with the Otsu's threshold renewedly to avoid losing area ，and the max connective region was extracted from the newly binary image. The experimental result indicated that the better precision，viz.74.6%，was obtained in the course of extracting the cotton binary template，and the arithmetic used for extracting cotton petals is robust.
Key Words：cotton；morphology；dark background；harvest；image segmentation；binary template 
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