The statistical analysis of plant part appearance - a review

被引:26
作者
Horgan, GW [1 ]
机构
[1] Biomath & Stat Scotland, Rowett Res Inst, Aberdeen AB21 9SB, Scotland
关键词
image analysis; eigenimage; eigenshape; discriminant analysis; image matching; crop cultivars; morphology;
D O I
10.1016/S0168-1699(00)00190-3
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
Visual appearance is widely used in assessing the variety or cultivar of crop samples, and in biological taxonomy in general. With computer storage capabilities becoming more easily accessible. image databases of plant specimens can be readily constructed. To make full use of this powerful facility, an important task is to compare different images. or to summarise them. This review addresses the question of how this may be done, given that images are stored as typically 10(5)-10(7) highly structured measurements. Image analysis is a wide subject area, and this review covers those parts of it which are relevant to this task. The task is subdivided into four (2 x 2) categories according to whether we are interested in outline shape only or in colour details. and whether the global position of object details is important, or only their local distribution. We refer to these approaches as local shape, global shape, colour distribution and colour detail (eigenimage analysis). As far as possible, we avoid a priori ideas regarding what features of objects are important, and seek methods which capture the full variability of their appearance. The techniques are illustrated by reference to work on carrots. (C) 2001 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:169 / 190
页数:22
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