Saliency detecting method applied to static image human segmentation

Abstract

The invention discloses a saliency detecting method applied to static image human segmentation. The method comprises the following steps of performing superpixel segmentation on a static image to be detected; performing face detection on the image after the superpixel segmentation to acquire a face area; performing skin color detection on the face area to acquire skin color information; performing color uniqueness calculation and color spatial distribution calculation according to the skin color information to acquire a color uniqueness value with the skin color information fused therein and a color spatial distribution value with the skin color information fused therein; performing saliency calculation according to the acquired color uniqueness value and the color spatial distribution value to acquire a saliency map used for static image human segmentation. Based on a conventional saliency detecting method, the method provided in the invention makes the skin color well detected by making the skin color information fused in the color uniqueness calculation and color spatial distribution calculation. The human skin color saliency is enhanced. Better and more accurate static image human segmentation effects are achieved. The method can be widely applied to the image processing field.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a saliency detection method applied to still image human body segmentation. Background technique [0002] A salient region in an image refers to the target region that is most concerned by human vision in a picture. Image saliency detection, as an important research topic in computer vision, is a technology that generates image saliency maps by analyzing salient regions in images based on features such as image color, intensity, direction, and edges. The saliency map generated by image saliency detection can be used in many image processing fields such as retrieval of similar images, image and video compression, detection of specific objects in images, image and video segmentation, etc., thereby improving the performance of image processing and promoting these fields. development of. [0003] Most of the current image saliency detection algorithms assign higher saliency values ​...

AI Technical Summary

Problems solved by technology

[0003] Most of the current image saliency detection algorithms assign higher saliency values ​​to areas with prominent image features and concentrated distribution, and lower saliency values ​​to other areas to facilitate subsequent image processing, but this method is not suitable for static images. Human Body Segmentation of Images

Human skin color is an indispensable part of human body segmentation, but human skin color does not appear very prominent in static images, and the distribution of skin color is wide, and the saliency value in image saliency detection is not high, so if the traditional saliency detection is still used method, in the later stage of human body segmentation, part of the skin color is often removed due to the low saliency value, which seriously affects the human body segmentation effect of static images

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