Image segmentation method based on annotated image learning

Abstract

The invention provides an image segmentation method based on an annotated image learn. The method comprises two processes of: 1, learning an annotated training sample, namely segmenting the training image, performing scene classification on the training image, and establishing connection between the annotated words and the segmentation region on a special scene; and 2, determining the annotated words of the region to be segmented according to a model parameter acquired by learning in the process 1, performing information fusion according to the annotated information of the region and finishing segmentation. According to the method, the image segmentation and the identification process are fused by learning the annotated image; the annotated words serve as connecting link of the image segmentation and object identification; connection is established between low-grade visual stimulation and the annotated words representing high-grade semantic information to guide the image segmentation process, so that the cognitive ability of the image segmentation result is improved. The method can be directly applied to the actual application fields such as automatic image annotation, computer-aided diagnosis of a medical image, segmentation and classification of remote sensing images, multimedia information retrieval and the like.

Description

technical field [0001] The invention relates to an image segmentation method. Specifically, it is a method to apply the object recognition problem in the image to the image segmentation problem through the study of a large number of reliable labeled images, through the relationship between the appearance visual features of things and the labeled words. Background technique [0002] In the past, people often separated the research of image segmentation and recognition, and image segmentation was basically used as a preprocessing stage of image understanding. Although many segmentation methods exist, the current technology cannot achieve satisfactory application results. Image segmentation has become a bottleneck restricting many vision applications, the reason is that when image is segmented, the visual similarity of image pixels and the correlation of adjacent pixel positions are mainly relied on as the basis for segmentation. This method that only relies on low-level visu...

AI Technical Summary

Problems solved by technology

This method that only relies on low-level visual features for segmentation has been difficult to achieve breakthroughs

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