Improved kernel density peak clustering method for plant image segmentation
A technology of image segmentation and kernel density, applied in the field of image processing, can solve problems such as DPC method can not obtain satisfactory clustering results, wrong allocation, etc.
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[0035] For ease of understanding, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of them. Example. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.
[0036] like figure 1 As shown, the present invention proposes an improved kernel density peak clustering method for plant image segmentation, the method comprising:
[0037] Input the image to be segmented,
[0038] Based on the local density ρ and the high density minimum distance δ in the density peak clustering DPC algorithm, the center point of the data set is selected to generate a decision map;
[003...
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