Ultra-pixel-based automatic segmentation method in dynamic outdoor environment

Abstract

The invention provides an ultra-pixel-based automatic segmentation method in a dynamic outdoor environment. The ultra-pixel-based automatic segmentation method mainly comprises the steps of calculating low-texture super pixels, generating a threshold hue image by using an Otsu method, estimating background distribution, allocating pixel tags and creating a mask. According to the ultra-pixel-based automatic segmentation method, an image is converted into a hue-saturation value color space and is segmented into super pixels, the super pixels are calculated by using an energy-driven sampling method, the threshold hue image is generated by using the Otsu method, probability distribution of background pixels is estimated by utilizing a super pixel group, the hue image is compared with the probability distribution to generate the pixel tags, and finally a mask image including regions of objects of interest and background objects is created. The ultra-pixel-based automatic segmentation method utilizes the low-texture super pixels, and generates the threshold hue image by using the Otsu method, so that precise segmentation can be carried out in the case of unstable lighting condition, the algorithm is simple and the precision is improved to some extent.

Description

technical field [0001] The invention relates to the field of image segmentation, in particular to an automatic segmentation method in a dynamic outdoor environment based on superpixels. Background technique [0002] In the research and application of images, people are often interested in some parts of the image, and these parts of interest correspond to specific areas with special properties in the image, which we call the target or foreground, and other parts become the image background. In order to identify and distinguish the target, we need to isolate the target from the image, which is image segmentation. In agriculture, this technology can be used in resource census, agricultural planning, crop yield estimation, pest detection, forest survey and many other aspects; in medicine, it can also be used for segmentation and extraction of lesions, so as to be used in clinical research and treatment. However, in the existing technology, since the data collection is often ca...

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Problems solved by technology

[0004] Aiming at the problem of unstable lighting conditions, the purpose of the present invention is to provide an automatic segmentation method based on superpixels in a dynamic outdoor environment. First, the image is converted into a hue-saturation value color space, and then segmented into superpixels, using The energy-driven sampling method calculates superpixels, then uses the maximum between-class variance method to generate a threshold tone image, then uses the set of superpixels to estimate the probability distribution of background pixels, compares the tone image to the distribution, generates pixel labels, and finally creates and the mask image of the region of the background object

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