Automatic digging method for remarkable objects of color images

A technology in color images and images, applied in image analysis, image data processing, instruments, etc., can solve the problem of no color image segmentation algorithm, achieve the effect of improving quality and overcoming manual interaction

Active Publication Date: 2013-03-13
SERCOMM ELECTRONICS SUZHOU CO LTD
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  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

[0014] It can be seen that there is still no general color image segmentat

Method used

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  • Automatic digging method for remarkable objects of color images
  • Automatic digging method for remarkable objects of color images
  • Automatic digging method for remarkable objects of color images

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0059] Example: see attached figure 1 As shown, an automatic extraction method of salient objects in color images, including:

[0060] 1. Acquisition of significant areas:

[0061] Input the image to be processed, transform the image from the RGB color space to the HSV color space, and obtain each feature map:

[0062]

[0063] After transforming the color model through the formulas (1), (2), and (3), the features such as chromaticity and brightness of the image are removed from the mean value to obtain the corresponding feature map, and the spectral residual hypothesis is used to make each feature map as follows deal with:

[0064] (4)

[0065] in, represents a Gaussian filter, is the inverse Fourier transform, is the logarithmic spectrum after Fourier transform, is the magnitude spectrum, is the average filter, . The three feature maps are fused according to the following formula to obtain a rough saliency map S map .

[0066] ...

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Abstract

The invention discloses an automatic digging method for remarkable objects of color images. The automatic digging method for the remarkable objects of the color images is characterized by comprising the steps of changing a red green blue (RGB) color space of the images into a hue saturation value (HSV) color space and calculating significance of targets in the aspects of hue, saturation and warm color gain; obtaining a rectangular frame surrounding a significance region according to a significance level image and performing rectangular frame expansion, wherein images surrounded by the expanded rectangular frame serve as follow-up processing images; using an improved watershed algorithm to pre-divide input image contents, using pre-divided super pixel subregions to replace weighted graphs formed by dividing pixel point structural graph, and adopting a maximum flow-minimum dividing strategy to perform division till energy functions are converged to obtain divided images. By means of an automatic image digging technology, the remarkable objects in scene can be quickly and effectively dug, and digging efficiency, the quality and the like are improved remarkably.

Description

technical field [0001] The invention relates to the problem of image segmentation, in particular to a method for automatic segmentation and extraction of salient objects or regions in color images. Background technique [0002] Among all human perceptions of the outside world, vision is the most important means. Through vision, humans and animals can perceive the size, brightness, and color of external objects, and obtain various information that is of great significance to the survival of the organism. According to statistics, 80% of the information that humans perceive the outside world comes from vision, such as images, graphics, videos, and texts. Since the advent of the computer, how to use the computer to simulate the human mechanism to reasonably process and analyze the information, so as to achieve the goal of serving human beings, has always been a key concern in this field. [0003] Image segmentation is a key step from image processing to image analysis. It repr...

Claims

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Application Information

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IPC IPC(8): G06T7/00
Inventor 刘纯平苏金玲龚声蓉林卉季怡蒋德茂
Owner SERCOMM ELECTRONICS SUZHOU CO LTD
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