Contents	6
	1 Introduction ??????????????	8
	1.1 Plant Species and Their Identification	8
	1.2 The Delimitation of Species by Descriptions	12
	1.3 Using Leaves to Diagnose Species	13
	1.4 Computational Botany	15
	1.5 Aims and Objectives	16
	2 Morphometrics: A Brief Review ??????????????	17
	2.1 Historical Background to Morphometrics	18
	2.1.1 Phase 1: Classical Taxonomy, Evolutionary Theory and Biometry: The Background for Morphometrics	18
	2.1.2 Phase 2: Genetics and Statistical Methods in Evolution, Agronomy and Biosystematics	20
	2.1.3 Phase 3: Multivariate Statistics and Morphometrics	21
	2.1.4 Phase 4: Geometric Morphometrics	23
	2.2 Morphometric Analysis of Leaves	25
	2.2.1 Analysis of Conventional Botanical Descriptors	26
	2.2.2 Analysis of Leaf Outline Shape	27
	2.2.3 Analysis of Leaf Margin Patterns	29
	2.2.4 Analysis of Homologous Landmarks and Semi-landmark Configurations	29
	2.2.5 Fractal Dimensions and Polygon Fitting	30
	2.2.6 Analysis of Leaf Venation Patterns	30
	2.2.7 Analysis of Leaf Texture	31
	2.2.8 Analysis of Other Features of the Leaf Blade	31
	2.3 Morphometrics of Flowers and Other Plant Organs	31
	2.4 Applications	33
	2.4.1 General-Purpose Species Identification	33
	2.4.2 Agriculture	35
	2.4.3 Intraspecific Variation, Geographical Distribution, Climate, Phylogeny	36
	2.5 Summary	37
	3 Feature Extraction ??????????????	39
	3.1 Leaf Shape	39
	3.1.1 Study of Existing Techniques for Leaf Shape Analysis	40
	3.1.2 Evaluation and Results	43
	3.2 Leaf Texture	44
	3.2.1 Macro-texture	45
	3.2.2 Micro-texture	46
	3.3 Margin Characteristics	50
	3.3.1 Extracting the Margin	51
	3.4 Locating the Apex and Insertion Point	53
	3.4.1 Dynamic Time Warping	53
	3.4.2 Finding the Points of Margin Symmetry	55
	3.5 Venation Patterns	55
	3.5.1 Extraction by Evolved Vein Classifiers	56
	3.5.2 Extraction by Ant Colonies	59
	3.5.3 Results and Comparison of Methods	61
	3.6 Summary	62
	4 Machine Learning for Plant Leaf Analysis ??????????????	63
	4.1 Incorporating Intra-species Variation into Plant Classification	63
	4.1.1 Utilizing the Hungarian Algorithm for Improved Classification of Leaf Blades	64
	4.1.2 Comparing Leaf Margins Using Dynamic Time Warping	74
	4.2 Combining Different Leaf Features	75
	4.2.1 Probabilistic Classification from K-Nearest-Neighbour	76
	4.2.2 Automatic Feature Selection	79
	4.3 Summary	84
	5 Botanists' Vision ??????????????	86
	5.1 Comparing the Eye Movements of Botanists and Non-Botanists	87
	5.1.1 Results and Analysis	88
	5.2 Reverse Engineering of Expert Visual Observations	91
	5.2.1 Related Work	92
	5.2.2 Methodology	93
	5.2.3 Evaluation	97
	5.2.4 Summary	100
	References ??????????????	101
	Index	114