CN107067382A - A kind of improved method for detecting image edge - Google Patents
A kind of improved method for detecting image edge Download PDFInfo
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- CN107067382A CN107067382A CN201710328075.6A CN201710328075A CN107067382A CN 107067382 A CN107067382 A CN 107067382A CN 201710328075 A CN201710328075 A CN 201710328075A CN 107067382 A CN107067382 A CN 107067382A
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- 238000000034 method Methods 0.000 title claims abstract description 21
- 238000001514 detection method Methods 0.000 claims abstract description 11
- 238000001914 filtration Methods 0.000 claims abstract description 7
- 230000009977 dual effect Effects 0.000 claims abstract description 4
- 230000001629 suppression Effects 0.000 claims abstract description 4
- 239000013598 vector Substances 0.000 claims description 6
- 238000003780 insertion Methods 0.000 claims description 3
- 230000037431 insertion Effects 0.000 claims description 3
- 239000011159 matrix material Substances 0.000 claims description 3
- 238000009795 derivation Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000003708 edge detection Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/73—Deblurring; Sharpening
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/40—Image enhancement or restoration using histogram techniques
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/70—Denoising; Smoothing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20024—Filtering details
- G06T2207/20032—Median filtering
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Abstract
The invention discloses a kind of improved method for detecting image edge, comprise the following steps：S1：Image is smoothed, noise is suppressed using improved median filter；S2：By x, y, 45 °, the first-order partial derivative on 135 ° of directions obtains difference both horizontally and vertically, and then try to achieve gradient magnitude and gradient direction；S3：Non-maxima suppression is carried out to gradient magnitude；S4：High threshold and Low threshold are obtained using histogram of gradients, rim detection then is carried out to image using dual threashold value-based algorithm；S5：Edge contrast, and edge is connected, obtain final edge image.The present invention replaces gaussian filtering using cum rights medium filtering, asks gradient magnitude and direction using the partial derivative of four direction, high-low threshold value is determined using histogram of gradients, it this method reduce false drop rate, improve accuracy of detection so that edge image profile becomes apparent from, and continuity is better.
Description
Technical field
Present invention relates particularly to a kind of improved method for detecting image edge.
Background technology
Image border refers to that its surrounding pixel gray scale is discontinuous or set of pixel of great change, is also target, the back of the body
Line of demarcation between scape and region.Marginal point in rim detection detection image first, it is then tactful by marginal point according to certain
Edge line is connected into, cut zone is finally constituted.Rim detection is feature extraction, target identification, the basis of image understanding, because
This, it is the basic problem of image procossing and computer vision.Image Edge-Detection mainly passes through derivation operator, Mathematical Morphology
Learn, four kinds of technologies such as wavelet transformation and image co-registration are realized, wherein derivation operator mode is most commonly used rim detection skill
Art, including Roberts operators, Sobel operators, Prewitt operators, Laplace operators and Log operators etc., these operators are simple
It is easily achieved, preferably, but to the interference sensitivity of noise, anti-interference is poor for real-time, and edge is easily by noise pollution, detection effect
It is really undesirable.
The content of the invention
The technical problem to be solved in the present invention is to provide a kind of improved method for detecting image edge.
A kind of improved method for detecting image edge, comprises the following steps：
S1：Image is smoothed, noise is suppressed using improved median filter；
S2：By x, y, 45 °, the first-order partial derivative on 135 ° of directions obtains difference both horizontally and vertically, and then try to achieve ladder
Spend amplitude and gradient direction；
S3：Non-maxima suppression is carried out to gradient magnitude；
S4：High threshold and Low threshold are obtained using histogram of gradients, rim detection then is carried out to image using dual threashold value-based algorithm；
S5：Edge contrast, and edge is connected, obtain final edge image.
Further, step S1 specific method is as follows：
1）An independent weights are distributed for each position in filter field, the distribution of weights is by weight matrixTo determine；Exist in filtering calculating process, each pixel valueBe inserted into the pixel of extension to
In amount, insertion number of times is its weights, spread vector is：, wherein,；
This pixel vectors is ranked up, then centered on some pixel, chosenSquare Neighborhood, by each picture in neighborhood
Plain gray value size is ranked up；
2）Median y is calculated according to equation below；
；
3）Made comparisons with middle output valve and surrounding pixel gray value, the larger pixel value of difference is revised as connecing with surrounding pixel
Near value, to realize the target for eliminating noise spot.
Further, step S2 specific method is as follows：
1）Calculate the first-order partial derivative on x, y, 45 °, 135 ° of directions：
X directions：；
Y directions：；
45 ° of directions：；
135 ° of directions：；
2）The difference tried to achieve both horizontally and vertically by the partial derivative of above four direction is：
；
；
3）Gradient magnitude g and gradient direction are tried to achieve respectively：
；
。
The beneficial effects of the invention are as follows：
The present invention replaces gaussian filtering using cum rights medium filtering, and gradient magnitude and direction are asked using the partial derivative of four direction,
High-low threshold value is determined using histogram of gradients, false drop rate is this method reduce, accuracy of detection is improved so that edge image profile
Become apparent from, continuity is better.
Embodiment
The present invention is further elaborated for specific examples below, but not as a limitation of the invention.
A kind of improved method for detecting image edge, comprises the following steps：
S1：Image is smoothed, noise is suppressed using improved median filter；
S2：By x, y, 45 °, the first-order partial derivative on 135 ° of directions obtains difference both horizontally and vertically, and then try to achieve ladder
Spend amplitude and gradient direction；
S3：Non-maxima suppression is carried out to gradient magnitude；
S4：High threshold and Low threshold are obtained using histogram of gradients, rim detection then is carried out to image using dual threashold value-based algorithm；
S5：Edge contrast, and edge is connected, obtain final edge image.
Step S1 specific method is as follows：
1）An independent weights are distributed for each position in filter field, the distribution of weights is by weight matrixTo determine；Exist in filtering calculating process, each pixel valueBe inserted into the pixel of extension to
In amount, insertion number of times is its weights, spread vector is：, wherein,；
This pixel vectors is ranked up, then centered on some pixel, chosenSquare Neighborhood, by each picture in neighborhood
Plain gray value size is ranked up；
2）Median y is calculated according to equation below；
；
3）Made comparisons with middle output valve and surrounding pixel gray value, the larger pixel value of difference is revised as connecing with surrounding pixel
Near value, to realize the target for eliminating noise spot.
Step S2 specific method is as follows：
1）Calculate the first-order partial derivative on x, y, 45 °, 135 ° of directions：
X directions：；
Y directions：；
45 ° of directions：；
135 ° of directions：；
2）The difference tried to achieve both horizontally and vertically by the partial derivative of above four direction is：
；
；
3）Gradient magnitude g and gradient direction are tried to achieve respectively：
；
。
Claims (3)
1. a kind of improved method for detecting image edge, it is characterised in that comprise the following steps：
S1：Image is smoothed, noise is suppressed using improved median filter；
S2：By x, y, 45 °, the first-order partial derivative on 135 ° of directions obtains difference both horizontally and vertically, and then try to achieve ladder
Spend amplitude and gradient direction；
S3：Non-maxima suppression is carried out to gradient magnitude；
S4：High threshold and Low threshold are obtained using histogram of gradients, rim detection then is carried out to image using dual threashold value-based algorithm；
S5：Edge contrast, and edge is connected, obtain final edge image.
2. method for detecting image edge according to claim 1, it is characterised in that step S1 specific method is as follows：
1）An independent weights are distributed for each position in filter field, the distribution of weights is by weight matrixTo determine；Exist in filtering calculating process, each pixel valueBe inserted into the pixel of extension to
In amount, insertion number of times is its weights, spread vector is：, wherein,；
This pixel vectors is ranked up, then centered on some pixel, chosenSquare Neighborhood, by each picture in neighborhood
Plain gray value size is ranked up；
2）Median y is calculated according to equation below；
；
3）Made comparisons with middle output valve and surrounding pixel gray value, the larger pixel value of difference is revised as connecing with surrounding pixel
Near value, to realize the target for eliminating noise spot.
3. method for detecting image edge according to claim 1, it is characterised in that step S2 specific method is as follows：
1）Calculate the first-order partial derivative on x, y, 45 °, 135 ° of directions：
X directions：；
Y directions：；
45 ° of directions：；
135 ° of directions：；
2）The difference tried to achieve both horizontally and vertically by the partial derivative of above four direction is：
；
；
3）Gradient magnitude g and gradient direction are tried to achieve respectively：
；
。
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| CN201710328075.6A CN107067382A (en) | 2017-05-11 | 2017-05-11 | A kind of improved method for detecting image edge |
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| CN109801428A (en) * | 2018-12-20 | 2019-05-24 | 深圳怡化电脑股份有限公司 | Detection method, detection device and the terminal of bank note edge line |
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