Tooth image segmentation method combined with C-V level set and GrabCut algorithm

Abstract

The invention provides a segmentation method combined with a C-V level set and a GrabCut algorithm. The method comprises the steps that a tooth image is preprocessed by image histogram information anda morphological method to highlight the contour of a target tooth; the contour of the target tooth is acquired through a C-V level set method, and is marked as a binary image; the binary image undergoes pyramidal up-sampling and down-sampling and is stored separately as the mask of the GrabCut algorithm; and the GrabCut algorithm is directly used to acquire the target tooth. Tooth segmentation iscarried out by combining the C-V level set with GrabCut, which effectively overcomes the segmentation difficulties of the tooth image with uneven grayscale distribution and crown adhesion. The segmentation method provided by the invention has the advantages of better segmentation effect and higher segmentation accuracy, and the average deviation degree of segmentation is 0.0198.

Description

technical field [0001] The invention belongs to the field of digital image segmentation and discloses a segmentation method for dental X-ray images. Background technique [0002] With the development of digital image technology, identification technology based on biometrics has increasingly become a research hotspot. The identification of unknown corpses by the public security and judicial organs has also become a major problem. Generally, the corpse is kept for a short time, and facial features, fingerprints, irises, etc. will be damaged to varying degrees, so it is impossible to accurately identify the identity of the corpse. DNA identification is accurate, but expensive and time-consuming. Teeth are a biological feature that is not easy to be destroyed. The enamel on its surface has the characteristics of strong high temperature resistance and corrosion resistance, and the teeth of different people not only have the characteristics of the occlusal state of the upper and...

AI Technical Summary

Problems solved by technology

[0004] In order to overcome the problems in the prior art of imperfect segmentation of dental X-ray images with defects such as uneven gray distribution, mutual adhesion of crown parts, and various noises in the image itself, the present invention proposes a combination of C-V level set and GrabCut Combined Image Segmentation Methods

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