CN109829928A - A kind of extracting method of target image extracting method and picture position feature - Google Patents
A kind of extracting method of target image extracting method and picture position feature Download PDFInfo
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- CN109829928A CN109829928A CN201811643829.8A CN201811643829A CN109829928A CN 109829928 A CN109829928 A CN 109829928A CN 201811643829 A CN201811643829 A CN 201811643829A CN 109829928 A CN109829928 A CN 109829928A
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- 238000000034 method Methods 0.000 title claims abstract description 37
- 230000011218 segmentation Effects 0.000 claims abstract description 13
- 238000010606 normalization Methods 0.000 claims description 4
- 230000009286 beneficial effect Effects 0.000 abstract description 3
- 238000000605 extraction Methods 0.000 description 10
- 239000000284 extract Substances 0.000 description 4
- 230000000694 effects Effects 0.000 description 3
- 235000013399 edible fruits Nutrition 0.000 description 2
- 238000004904 shortening Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 1
- 230000001788 irregular Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
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Abstract
The present invention is suitable for technical field of image processing, provides the recognition methods of a kind of target image extracting method and picture position feature, and target image extracting method includes: to carry out gray proces to original image, obtains image one；Threshold segmentation is carried out based on threshold value a pair of image one, image two is obtained, closed edge contour is extracted in image two；Threshold segmentation is carried out to image two based on threshold value two, obtain target image, threshold value two is the edge contour enclosing region area of target image and the ratio of edge contour perimeter, target image extracting method provided by the invention has the following beneficial effects: that edge contour is carried out after one segmented image of threshold value to be mentioned, suitable profile sieve is filtered out further according to target object shape, ensure that the accuracy of image procossing.
Description
Technical field
The invention belongs to technical field of image processing, a kind of target image extracting method and picture position feature are provided
Extracting method.
Background technique
Picture position is characterized in extracting what the edge designs for being all based on target object were applicable in out based on prior art image
Threshold value or threshold value is arranged based on area grayscale value, there are the interference of the imperfect band of marginal information or similar background to lead
The problem of cause.
Summary of the invention
The embodiment of the present invention provides a kind of target image extracting method, it is intended to improve the precision of target image extraction.
In order to solve above-mentioned purpose, the present invention provides a kind of target image extracting method, and the method is based on image side
The information of edge and object region is denoised, and target image is obtained.
Further, the step S1 specifically comprises the following steps:
S11, gray proces are carried out to original image, obtains image one；
S12, Threshold segmentation is carried out based on threshold value a pair of image one, obtains image two, closed side is extracted in image two
Edge profile；
S13, Threshold segmentation is carried out to image two based on threshold value two, obtains target image, threshold value two is the side of target image
The ratio of edge profile enclosing region area and edge contour perimeter.
Target image extracting method provided by the invention, which has the following beneficial effects:, carries out side after one segmented image of threshold value
Edge profile mentions, and filters out suitable profile further according to target object shape and sieves, ensure that the accuracy of image procossing；
In order to solve above-mentioned purpose, the present invention provides a kind of picture position feature extraction side based on the target image
Method, described method includes following steps:
S14, coordinate of all pixels point in image coordinate system in target image region is calculated；
S15, position feature of the target image in image coordinate system, institute's rheme are calculated based on normalization geometry Moment Methods
Feature is set to be made of the centre coordinate of target image and the drift angle of target image.
Picture position feature of the invention is divided into two parts during the extraction process: utilizing image border and object region
Information extracts accurately target image；Target image region is only traversed, to calculate picture position feature, relative to whole
The ratio of a image-region, region shared by target image is small, greatly subtracts the extraction time for shortening image object feature.
Detailed description of the invention
Fig. 1 is target image extracting method flow chart provided in an embodiment of the present invention；
Fig. 2 is the effect provided in an embodiment of the present invention based on image extraction method square shaped target image provided by the invention
Fruit comparison diagram；
Fig. 3 is feature extracting method flow chart in picture position provided in an embodiment of the present invention.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.
Fig. 1 is target image extracting method flow chart provided in an embodiment of the present invention, and this method is based on image border and mesh
Logo image area information is denoised, and target image is obtained.
This method is specific as follows:
S11, gray proces are carried out to original image, obtains image one；
S12, Threshold segmentation is carried out based on threshold value a pair of image one, obtains image two, closed side is extracted in image two
Edge profile；
In embodiments of the present invention, threshold value carries out threshold value point based on threshold value a pair of image one first is that histogram method is obtained
It cutting, eliminates most of noise in background, the noise as similar in brightness and target object not can be removed, extract figure
As in closed edge contour, partially it is made of noise.
S13, Threshold segmentation is carried out to image two based on threshold value two, obtains target image, threshold value two is the side of target image
The ratio of edge profile enclosing region area and edge contour perimeter；
In embodiments of the present invention, Threshold segmentation is carried out to image again based on threshold value two, brightness and target can be removed
Noise similar in object, obtains target image.
Target image extracting method provided by the invention, which has the following beneficial effects:, carries out side after one segmented image of threshold value
Edge profile mentions, and filters out suitable profile further according to target object shape and sieves, ensure that the accuracy of image procossing.
Canny algorithm, Grabcut foreground segmentation, Threshold segmentation scheduling algorithm on probation, above-mentioned algorithm are handling specific image
Effect is very outstanding, and the image conditions of actual photographed are more complicated, and the exclusive use of each algorithm is just difficult to obtain ideal process
As a result, time-consuming in the case where the use that simply combines will increase much again, Fig. 2 provides the extraction effect of rectangular target image
Fruit figure, based on the extraction that target image extracting method provided by the invention carries out, Fig. 2 (a) is provided for the present invention to original image
Image one after carrying out gray proces, Fig. 2 (b) are to based on the image two after the progress Threshold segmentation of threshold value a pair of image one, Fig. 2
(c) after to carry out Threshold segmentation to image two based on threshold value two, the target image of extraction.
Fig. 3 is feature extracting method flow chart in picture position provided in an embodiment of the present invention, and this method is based on step S11 extremely
Step S13 extracts target image, carries out following steps for target image:
S14, coordinate of all pixels point in image coordinate system in target image region is calculated；
S15, position feature of the target image in image coordinate system, institute's rheme are calculated based on normalization geometry Moment Methods
Feature is set to be made of the centre coordinate and target image drift angle of target image.
The position feature that image is extracted based on normalization geometry Moment Methods, can reduce the scaling of target image to feature
Location information influences, and accidentally influence of the noise region for picture position feature, if target area is irregular shape, resists
Interference performance is strong.
Picture position feature of the invention is divided into two parts during the extraction process: utilizing image border and object region
Information extracts accurately target image；Target image region is only traversed, to calculate picture position feature, relative to whole
The ratio of a image-region, region shared by target image is small, greatly subtracts the extraction time for shortening image object feature, target figure
As the precision extracted ensure that the precision of picture position feature.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Made any modifications, equivalent replacements, and improvements etc., should all be included in the protection scope of the present invention within mind and principle.
Claims (3)
1. a kind of target image extracting method, which is characterized in that the method is based on image border and object region
Information is denoised, and target image is obtained.
2. target image extracting method as described in claim 1, which is characterized in that the step S1 specifically comprises the following steps:
S11, gray proces are carried out to original image, obtains image one；
S12, Threshold segmentation is carried out based on threshold value a pair of image one, obtains image two, closed edge wheel is extracted in image two
It is wide；
S13, Threshold segmentation is carried out to image two based on threshold value two, obtains target image, threshold value two is the edge wheel of target image
The ratio of wide enclosing region area and edge contour perimeter.
3. a kind of picture position feature extracting method based on target image described in claims 1 or 2 any claim, special
Sign is that described method includes following steps:
S14, coordinate of all pixels point in image coordinate system in target image region is calculated；
S15, position feature of the target image in image coordinate system is calculated based on normalization geometry Moment Methods, the position is special
Sign is made of the centre coordinate of target image and the drift angle of target image.
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| CN107103298A (en) * | 2017-04-21 | 2017-08-29 | 桂林电子科技大学 | Chin-up number system and method for counting based on image procossing |
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| CN102034106A (en) * | 2010-12-20 | 2011-04-27 | 浙江工业大学 | Image treatment-based method for extracting flame outline |
| CN102999897A (en) * | 2011-09-19 | 2013-03-27 | 香港中文大学 | Method and device for sea surface oil spillage detection based on SAR (synthetic aperture radar) image |
| CN103577825A (en) * | 2012-07-25 | 2014-02-12 | 中国科学院声学研究所 | Automatic target identification method and system for synthetic aperture sonar image |
| CN104754340A (en) * | 2015-03-09 | 2015-07-01 | 南京航空航天大学 | Reconnaissance image compression method for unmanned aerial vehicle |
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Application publication date: 20190531 |