Kinect depth image inpainting method based on improved trilateral filtering

A technology of depth image and restoration method, applied in image enhancement, image data processing, instrument and other directions, can solve the problems of inability to accurately measure the cavity area, poor restoration effect, mismatch between depth map and color map edge, etc., and achieve good cavity Filling effect, good hold effect

Inactive Publication Date: 2015-07-29
HARBIN ENG UNIV
View PDF2 Cites 29 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the limitations of Kinect's structural characteristics and ranging principle, the obtained depth image has some defects: such as the hollow area caused by the inability to accurately measure the depth value, and the edge mismatch between the depth image and the color image, etc.
[0004] At present, there are mainly two methods for Kinect depth image restoration: one method is to repair the depth image directly without texture image, and its restoration effect is poor; The information of the texture image, this type of method has a good effect on maintaining the edge of the depth map

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Kinect depth image inpainting method based on improved trilateral filtering
  • Kinect depth image inpainting method based on improved trilateral filtering
  • Kinect depth image inpainting method based on improved trilateral filtering

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0044] The present invention will be further described below in conjunction with the accompanying drawings.

[0045] This method uses an improved trilateral filtering method that combines color difference and structural similarity coefficients to repair the depth map, and effectively preserves depth edge information while filling holes in the depth map.

[0046] The depth map restoration method based on improved trilateral filtering includes the following steps.

[0047] S1 uses kinect depth sensor to acquire depth image and color image synchronously;

[0048] S2 aligns the color map and the depth map;

[0049] S3 extracts the edge information of the depth map Depth_edge(i,j);

[0050] S4 extracts color image edge information Color1_edge(i,j);

[0051] S5 removes the non-boundary texture information in Color1_edge(i,j) of the edge of the color image contour. Firstly, Euclidean distance transformation is performed on the edge of the depth map, and all edge points in the edg...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention belongs to the technical field of depth image inpainting, and particularly relates to a Kinect depth image inpainting method based on improved trilateral filtering for kinect depth images. The method comprises the steps that depth images and color images are synchronously acquired by utilizing Kinect; the color images and the depth images are aligned; edge information of the depth images is extracted; edge information of the color images is extracted; non-boundary texture information in the color images is removed; pixel points of which the depth values are incorrect are found in the depth images by using a region growing method and the incorrect depth values of the points are removed; and filling inpainting is performed on the hole areas of the depth images by using the improved trilateral filtering method based on aberration and structural similarity coefficient. The method has great hole filling effect for the kinect depth images so that the edge information of the depth images can be greatly maintained.

Description

technical field [0001] The invention belongs to the technical field of depth image repair, and in particular relates to a Kinect depth image repair method based on improved trilateration filtering for kinect depth images. Background technique [0002] Depth image is a new image mode, which has broad application prospects in computer vision, automatic navigation and other fields. [0003] As a relatively cheap depth image and color image acquisition device, Kinect acquires depth images through special structured light technology, and obtains depth images with high resolution, which has attracted the general attention of scientific research and development workers and the industry. However, due to the limitations of Kinect's structural characteristics and ranging principle, the obtained depth image has some defects: such as the hollow area caused by the inability to accurately measure the depth value, and the edge mismatch between the depth image and the color image. These pr...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
Inventor 项学智徐旺旺南长君白二伟王猛包文龙葛长赟张磊乔玉龙
Owner HARBIN ENG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap