Multi-shape-prior level set independent component analysis method and image partitioning system

Abstract

The invention belongs to the field of image processing technology and discloses a multi-shape-prior level set independent component analysis method and an image partitioning system. The method comprises the steps that a to-be-partitioned image and shape priors are input; curve initialization is performed; shape prior alignment is performed; the aligned shape priors are coded through a level set function; a shape prior matrix is formed; independent component analysis is used to perform dimension reduction; the current level set function is projected to a low-dimension space; probability distribution of the shape priors is estimated, shape driving energy items are constructed and combined with data driving energy items, and an energy function is formed; and the energy function is minimized,curve evolution is driven, and a partitioning result is obtained. Through the method and the system, high-dimension redundant features of the shape priors can be eliminated, therefore, distribution ofthe shape priors can be subjected to more accurate statistical analysis, more effective shape constraint can be formed, and finally an accurate partitioning result can be obtained.

Description

Technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to an independent component analysis multi-shape prior level set method and an image segmentation system. Background technique [0002] In the past half-century, image segmentation has always attracted people's attention and maintained a long-lasting research interest. So far, thousands of segmentation methods based on different theories have been proposed. Among them, the method based on active contour model adopts prior knowledge to guide the segmentation process and provides a unified framework for segmentation. It is a very popular segmentation method currently studied. Fundamentally speaking, the active contour model method can be divided into two types: parametric and geometric. Parametric refers to the curve or surface that directly expresses the deformation in the form of parameters; the geometric model is to embed low-dimensional curves or surfaces into high...

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Problems solved by technology

[0003] To sum up, the problem existing in the existing technology is: in the current method of introducing shape prior, for the single prior method, there is a single shape prior that cannot reflect the commonality of a class of shapes, when the difference between the target to be segmented and the shape prior When it is relatively large, the problem that better results cannot be obtained; for the multi-shape prior method, the prior shape is generally sparsely distributed in the high-dimensional feature space, it is difficult to accurately estimate the distribution of the shape prior, and the inaccurate distribution estimation Issues that can lead to inaccurate segmentation results

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