Complete extraction method of true color eye image graph white eye area

An extraction method, true color technology, applied in neural learning methods, acquisition/recognition of eyes, image enhancement, etc., can solve the problems of edge blurring or occlusion, edge disconnection threshold, inappropriateness and other problems of extraction of white eyes, and achieve accurate speed , fast speed, and the effect of improving accuracy

Active Publication Date: 2017-07-18
CAPITALBIO CORP
View PDF8 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, when using various edge detection algorithms, the problem of edge disconnection or inappropriate threshold will occ...

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
  • Complete extraction method of true color eye image graph white eye area
  • Complete extraction method of true color eye image graph white eye area
  • Complete extraction method of true color eye image graph white eye area

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0025] The present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.

[0026] Such as figure 1 , figure 2 Shown, the present invention provides a kind of complete extraction method of the white eye region of true color eye picture image, and it comprises the following steps:

[0027] 1) For the 24-bit true-color eye images from different angles of natural light, use the trained edge extraction model to extract the edges of the complete areas of white eyes and black eyes: use the trained deep neural network model that simulates the human brain to recognize edges to automatically Predict the outer edges of white eyes and black eyes in various 24-bit true-color eye image images, and obtain a nearly complete binary image of the overall outer edges of white eyes and black eyes in 24-bit true-color eye image images.

[0028] The deep neural network model is an edge extraction model, which includes multiple convolutional lay...

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 relates to a complete extraction method of a true color eye image graph white eye area. The method comprises the following steps of using a trained edge extraction model to carry out edge extraction of white-eye and black-eye complete areas on different-visual-angle 24-bit true color eye image graphs of natural light; after expansion and corrosion morphology conversion, acquiring a completely-enclosed edge binary image, calculating a maximum connection area, mapping the binary image to an original 24-bit true color eye image graph and acquiring the white-eye and black-eye complete areas; using a trained black-eye position prediction model to calculate position coordinate information of a black-eye external connection rectangle, and rapidly positioning a black-eye position; in the white-eye and black-eye complete areas, using the black-eye position coordinate information to roughly segment a black-eye area, using a Hough detection circle to calculate and acquire a black-eye center and a radius, and accurately segment the black-eye area; and according to visual angle orientation information of an eye image and the acquired black-eye area, removing a black-eye area image in the white-eye and black-eye complete areas and acquiring a white-eye area. In the invention, the white-eye area can be accurately, effectively and completely extracted.

Description

technical field [0001] The invention relates to a method for extracting an eye image map, in particular to a method for completely extracting the white eye region of a true-color eye image map. Background technique [0002] In the past year, deep convolutional neural networks have had epoch-making applications in image and speech recognition technology, especially in the direction of medical image prediction and diagnosis. Various achievements have been published. Medical image images are mainly grayscale images. Sclera recognition, iris recognition and fundus image recognition are mainly aimed at grayscale images and false color images. For the eye images that deal with natural light, we mainly extract and analyze the features in the eye images of the elderly and those with serious illnesses. However, when using various edge detection algorithms, the problem of edge disconnection or inappropriate threshold will occur, and the edge of the white eye extracted by traditional ...

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
IPC IPC(8): G06K9/00G06T7/13G06T5/30G06N3/08G06T7/11G06K9/62
CPCG06N3/08G06T5/30G06T2207/10024G06T2207/30041G06V40/193G06V40/18G06F18/24
Inventor 王文君侯博严张倩王东邢婉丽程京
Owner CAPITALBIO CORP
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