CN106097317A - A kind of many spot detection based on discrete cosine phase information and localization method - Google Patents
A kind of many spot detection based on discrete cosine phase information and localization method Download PDFInfo
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- CN106097317A CN106097317A CN201610392354.4A CN201610392354A CN106097317A CN 106097317 A CN106097317 A CN 106097317A CN 201610392354 A CN201610392354 A CN 201610392354A CN 106097317 A CN106097317 A CN 106097317A
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Abstract
The invention discloses a kind of many spot detection based on discrete cosine phase information and localization method, strengthen including the multiple target region using discrete cosine phase information, traversal threshold value maximum variance is used to carry out binarization segmentation and rim detection, and use many facula mass centers of image moment method to calculate, finally give edge and the barycenter of all hot spots.The present invention has taken into full account the phase information of discrete data, realizes image object detection.It is fast that the present invention calculates speed, and result is effective, reliably, it is adaptable to laser measurement, Robot visual location, the association area such as optical precision measurement.
Description
Technical field
The present invention relates to detection and the localization method of hot spot, a kind of spot detection based on digital picture and location
Method.
Background technology
Spot detection is a key in the accurate measurements such as laser collimator, laser measurement, optically measuring speeds, detection means
Technology, the precision of detection algorithm, calculate speed and directly affects the effect of optical measurement.Traditional spot detection has centroid method,
Median method and Hough transform method.The above two are the bigger error of easy generation in the case of light spot image skewness, and suddenly
Husband's conversion needs pointwise to vote, and record, amount of calculation is bigger, is also easily affected by noise.And the hot spot data in reality
It is easily subject to the interference of environment, there is the problems such as brightness irregularities, overexposure, noise.
Owing to image data information can be divided into useful information and redundancy, image is carried out discrete Fourier transform or
After person's discrete cosine transform, useful information and redundancy all presented in statistical information in frequency spectrum, and frequency spectrum is permissible
It is divided into amplitude spectrum and the form of phase spectrum sum.View data can be analyzed in terms of phase spectrum and amplitude spectrum two.
It is said that in general, phase spectrum comprises the texture information of image, and amplitude spectrum comprises the comparison of light and shade information of image.
Meanwhile, phase spectrum represents the positional information of data, and phase spectrum reconstruct can preserve the effective information of image, and amplitude spectrum reconstructs
The entire infrastructure feature of original image can be lost.
By the filtering of the phase spectrum of light spot image discrete message and reconstruct being realized the enhancing in common-denominator target region, enter
And use Binarization methods and centroid detection method, it may be determined that the shape of hot spot and position, thus provide number for accurate measurement
According to.
Summary of the invention
Goal of the invention: the problem existed for existing method, it is desirable to provide a kind of accurate, efficiently based on discrete
Many spot detection of cosine phase information and localization method.
Technical scheme: a kind of many spot detection based on discrete cosine phase information and localization method, comprises the steps:
S1: light spot image is carried out marking area based on phase spectrum and extracts pretreatment；
S2: pretreated light spot image is carried out binarization segmentation threshold calculations；
S3: the image obtaining step S2 carries out rim detection；
S4: the image obtaining step S3 carries out centroid calculation.
Further, marking area described in step S1 extract preprocess method particularly as follows:
S1.1: coloured image is carried out gray processing process；
S1.2: gray level image is carried out discrete cosine transform, extracts amplitude information and phase information；
S1.3: be filtered phase information, obtains the phase information difference before and after filtering；
S1.4: phase information difference amplitude information and S1.3 obtained carries out inverse discrete cosine transform, obtains reconstruct figure
Picture.
Further, the binarization segmentation threshold value calculation method described in S2 particularly as follows:
S2.1: setting gray level image gray level is L, then tonal range is [0, L-1], and the optimal threshold of image is:
T=Max [w0(t)·(u0(t)-u)2+w1(t)·(u1(t)-u)2]
Wherein, when the threshold value of segmentation is t, w0For background ratio, u0For background mean value, w1For prospect ratio, u1For prospect
Average, u is the average of entire image；
Make w0(t)·(u0(t)-u)2+w1(t)·(u1(t)-u)2The t that this transition formula evaluation is maximum, is segmentation image
Optimal threshold；
S2.2: the reconstruct image using this threshold value to obtain S1.4 is split, and obtains bianry image.
Further, the edge detection method described in S3 is particularly as follows: in bianry image, examine from left to right every a line
Survey, then detect every a line from top to bottom, find that the coordinate of pixel value change is i.e. designated as edge.
Further, the centroid computing method described in S4 is particularly as follows: calculate multiple connections of the bianry image that S2 obtains
The barycenter in territory, computational methods are as follows:
Zeroth order square:
First moment:
Wherein, V (i, j) represents coordinate i, the image pixel value at j, M and N representative image size, and the barycenter of image is designated as:
Beneficial effect: compared with prior art, a kind of based on discrete cosine phase information many hot spots that the present invention provides
Detection and localization method, calculate speed fast, it is possible to realize multiobject detection, strong interference immunity, it is adaptable to Laser Processing, man-machine
Interaction, the field such as optical detection.
Accompanying drawing explanation
Fig. 1 is the algorithm flow chart of the present invention.
Detailed description of the invention
Below by a most preferred embodiment and combine accompanying drawing the technical program is described in detail.
As it is shown in figure 1, a kind of many spot detection based on discrete cosine phase information and localization method, including walking as follows
Rapid:
S1: light spot image is carried out marking area based on phase spectrum and extracts pretreatment, specifically include following sub-step:
S1.1: coloured image is carried out gray processing process；
S1.2: gray level image is carried out discrete cosine transform, extracts amplitude information and phase information；
S1.3: be filtered phase information, obtains the phase information difference before and after filtering；
S1.4: phase information difference amplitude information and S1.3 obtained carries out inverse discrete cosine transform, obtains reconstruct figure
Picture.
S2: pretreated light spot image is carried out binaryzation calculating, specifically includes following sub-step:
S2.1: setting gray level image gray level is L, then tonal range is [0, L-1], and the optimal threshold of image is:
T=Max [w0(t)·(u0(t)-u)2+w1(t)·(u1(t)-u)2]
Wherein, when the threshold value of segmentation is t, w0For background ratio, u0For background mean value, w1For prospect ratio, u1For prospect
Average, u is the average of entire image；
Make w0(t)·(u0(t)-u)2+w1(t)·(u1(t)-u)2The t that this transition formula evaluation is maximum, is segmentation image
Optimal threshold；
S2.2: the reconstruct image using this threshold value to obtain S1.4 is split, and obtains bianry image；
S3: the image after step S2 is carried out rim detection, particularly as follows: in bianry image, to every a line from left to right
Detection, then detect every a line from top to bottom, find that the coordinate of pixel value change is i.e. designated as edge.
S4: image S3 carries out centroid calculation, calculates the barycenter of multiple connected domains of the bianry image that S2 obtains, calculating side
Method is as follows:
Zeroth order square:
First moment:
Wherein, (i, j) represents coordinate i to V, the image pixel value at j, M and N representative image size, and the barycenter of image is i.e. remembered
For:
Thus shape and the position of hot spot, the hot spot finally given in Fig. 1 is indicated by rim detection and centroid calculation
Shape and location, the shape of hot spot is edge, and location is the result of centroid calculation.
The present invention uses the centroid calculation of phase spectrum reconstruct and multiply connected domain to determine spot size and position, and algorithm is simple
Single, calculate speed fast, Detection results is good, and algorithm transplantability is good, can be effectively improved detection quality and the effect of hot spot.Below it is only
The preferred embodiment of the present invention, it should be pointed out that: for those skilled in the art, without departing from the present invention
On the premise of principle, it is also possible to make some improvements and modifications, these improvements and modifications also should be regarded as protection scope of the present invention.
Claims (5)
1. many spot detection based on discrete cosine phase information and localization method, it is characterised in that comprise the steps:
S1: light spot image is carried out marking area based on phase spectrum and extracts pretreatment；
S2: pretreated light spot image is carried out binarization segmentation threshold calculations；
S3: the image obtaining step S2 carries out rim detection；
S4: the image obtaining step S3 carries out centroid calculation.
A kind of spot detection method based on phase information the most according to claim 1, it is characterised in that institute in step S1
The marking area stated extract preprocess method particularly as follows:
S1.1: coloured image is carried out gray processing process；
S1.2: gray level image is carried out discrete cosine transform, extracts amplitude information and phase information；
S1.3: be filtered phase information, obtains the phase information difference before and after filtering；
S1.4: phase information difference amplitude information and S1.3 obtained carries out inverse discrete cosine transform, obtains reconstructing image.
A kind of spot detection method based on phase information the most according to claim 2, it is characterised in that institute in step S2
The binarization segmentation threshold value calculation method stated particularly as follows:
S2.1: setting gray level image gray level is L, then tonal range is [0, L-1], and the optimal threshold of image is:
T=Max [w0(t)·(u0(t)-u)2+w1(t)·(u1(t)-u)2]
Wherein, when the threshold value of segmentation is t, w0For background ratio, u0For background mean value, w1For prospect ratio, u1For prospect average,
U is the average of entire image；
Make w0(t)·(u0(t)-u)2+w1(t)·(u1(t)-u)2The t that this transition formula evaluation is maximum, is the optimal of segmentation image
Threshold value；
S2.2: the reconstruct image using this threshold value to obtain S1.4 is split, and obtains bianry image.
A kind of spot detection method based on phase information the most according to claim 1, it is characterised in that institute in step S3
The edge detection method stated is particularly as follows: in bianry image, detect from left to right every a line, then detects each from top to bottom
OK, find that the coordinate of pixel value change is i.e. designated as edge.
A kind of spot detection method based on phase information the most according to claim 1, it is characterised in that institute in step S4
The centroid computing method stated particularly as follows:
Calculating the barycenter of multiple connected domains of the bianry image that S2 obtains, computational methods are as follows:
Zeroth order square:
First moment:
Wherein, V (i, j) represents coordinate i, the image pixel value at j, M and N representative image size, and the barycenter of image is designated as:
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Cited By (7)
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| CN107133627A (en) * | 2017-04-01 | 2017-09-05 | 深圳市欢创科技有限公司 | Infrared light spot center point extracting method and device |
| CN107784669A (en) * | 2017-10-27 | 2018-03-09 | 东南大学 | A kind of method that hot spot extraction and its barycenter determine |
| CN110132150A (en) * | 2019-05-10 | 2019-08-16 | 公安部第三研究所 | The system and method for visible light source spot size test |
| CN110533601A (en) * | 2019-07-15 | 2019-12-03 | 江苏大学 | A kind of Position of Laser-Spot Center and profile acquisition methods |
| CN111855158A (en) * | 2020-07-31 | 2020-10-30 | 武汉华工激光工程有限责任公司 | Multi-spot light beam analysis method and device |
| CN112804447A (en) * | 2020-12-30 | 2021-05-14 | 北京石头世纪科技股份有限公司 | Method, device, medium and electronic equipment for detecting near-field object |
| CN115205317A (en) * | 2022-09-15 | 2022-10-18 | 山东高速集团有限公司创新研究院 | Bridge monitoring photoelectric target image light spot center point extraction method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107133627A (en) * | 2017-04-01 | 2017-09-05 | 深圳市欢创科技有限公司 | Infrared light spot center point extracting method and device |
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| CN110132150A (en) * | 2019-05-10 | 2019-08-16 | 公安部第三研究所 | The system and method for visible light source spot size test |
| CN110533601A (en) * | 2019-07-15 | 2019-12-03 | 江苏大学 | A kind of Position of Laser-Spot Center and profile acquisition methods |
| CN111855158A (en) * | 2020-07-31 | 2020-10-30 | 武汉华工激光工程有限责任公司 | Multi-spot light beam analysis method and device |
| CN112804447A (en) * | 2020-12-30 | 2021-05-14 | 北京石头世纪科技股份有限公司 | Method, device, medium and electronic equipment for detecting near-field object |
| CN112804447B (en) * | 2020-12-30 | 2023-01-17 | 北京石头创新科技有限公司 | Method, device, medium and electronic equipment for detecting near-field object |
| CN115205317A (en) * | 2022-09-15 | 2022-10-18 | 山东高速集团有限公司创新研究院 | Bridge monitoring photoelectric target image light spot center point extraction method |
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