WO2018010391A1 - 一种板卡的检测方法及装置 - Google Patents
一种板卡的检测方法及装置 Download PDFInfo
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- WO2018010391A1 WO2018010391A1 PCT/CN2016/113235 CN2016113235W WO2018010391A1 WO 2018010391 A1 WO2018010391 A1 WO 2018010391A1 CN 2016113235 W CN2016113235 W CN 2016113235W WO 2018010391 A1 WO2018010391 A1 WO 2018010391A1
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
- G06T7/001—Industrial image inspection using an image reference approach
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/40—Analysis of texture
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20036—Morphological image processing
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
Definitions
- the invention relates to the field of automatic optical detection, in particular to a method and a device for detecting a card.
- Automated optical inspection is an essential part of the industrial production process.
- the principle is to obtain the surface state of the finished product through optical imaging, and to detect foreign matter or surface defects on the finished product by image processing.
- determining whether the finished product enters the detection area is a key step of automatic optical detection.
- the telecentric lens is usually used in the detection.
- an object of the present invention is to provide a method and apparatus for detecting a card, which can accurately detect whether a card enters a detection area without requiring a high-precision structure.
- the invention provides a method for detecting a board, comprising the following steps:
- the template image is an area of the card in the detection area and the An image when the ratio of the area of the detection area is a predetermined ratio
- the image to be tested is binarized to obtain a binary image of the image to be tested;
- the method further includes:
- the boundary of the image to be tested is expanded, wherein the expanded portion is filled with pixels having a gray value of 0.
- the image to be tested is binarized to obtain a binary image of the image to be tested, and specifically includes:
- the method further includes:
- a morphological closing operation is performed on the binary image to perform morphological filling and noise cancellation on the binary image.
- the image to be tested is an image that the card enters the detection area for the first time.
- the predetermined ratio is 1/4.
- the invention also provides a detecting device for a card, comprising:
- An acquisition unit configured to collect an image to be tested of a detection area located on the conveyor belt
- a similarity matching unit configured to match the image to be tested with a preset template image to obtain a similarity between the image to be tested and the template image; wherein the template image is a card in the detecting An image when the ratio of the area within the area to the area of the detection area is a predetermined ratio;
- a binarization unit configured to perform binarization on the image to be tested when the similarity is less than a preset threshold, to obtain a binary image of the image to be tested
- a contour extracting unit configured to extract all contours on the binary image, calculate an area of the connected region surrounded by the contour, and obtain an area of a minimum circumscribed rectangle of the connected region having the largest area;
- a ratio calculating unit configured to determine that the card enters the detection area when a ratio of an area of the minimum circumscribed rectangle to an area of the binary image is greater than or equal to the predetermined ratio value.
- the method further comprises:
- an expansion unit configured to expand a boundary of the image to be tested, wherein the extended portion is filled with pixels with a gray value of 0.
- the binarization unit specifically includes:
- an HSV value calculation module configured to: when the similarity is less than a preset threshold, calculate an HSV value of each pixel of the image to be tested according to an RGB value of each pixel of the image to be tested, where , H is the hue, S is the saturation, and V is the value;
- a matching module configured to compare an HSV value of each pixel of the image to be tested with a preset HSV value of a board bottom color, and determine whether the pixel point matches a color of the board bottom layer; If yes, the gray value of the pixel is set to 1 on the image to be tested, and if not, the gray value of the pixel is set to 0 on the image to be tested;
- the difference between the H value of one pixel of the image to be tested and the H value of the color of the board substrate is less than a preset error, and the S value of the pixel of the image to be tested and the color of the board bottom layer
- the difference of the S value is smaller than the preset error, and the difference between the V value of the pixel of the image to be tested and the V value of the color of the board bottom layer is less than the preset error.
- the pixel of the image matches the color of the board backplane;
- the binary image generating module is configured to generate a binary image after the HSV value of all the pixels of the image to be tested is compared with the HSV value of the preset color of the board bottom color.
- the method further comprises:
- the morphological closing unit is configured to perform a morphological closing operation on the binary image to perform morphological filling and noise elimination on the binary image.
- the method and device for detecting a card provided by the embodiment of the present invention, after binarizing the image to be tested, according to the area of the minimum circumscribed rectangle of the connected area having the largest area on the binary image and the second The ratio of the area of the value image determines whether the card enters the detection area, so that it is possible to accurately determine whether the card enters the detection area without requiring a high-precision mechanical movement structure.
- FIG. 1 is a schematic flow chart of a method for detecting a card provided by an embodiment of the present invention.
- FIG. 2 is a schematic diagram of an image to be tested according to an embodiment of the present invention.
- 3(a) to 3(a) are schematic diagrams of template images provided by an embodiment of the present invention.
- FIG. 4 is a schematic diagram of a binary image provided by an embodiment of the present invention.
- Figure 5 is a schematic illustration of the minimum circumscribed rectangle defining the connected region having the largest area on the binary image.
- FIG. 6 is a schematic diagram of expanding the image to be tested of FIG. 2.
- Fig. 7 is a schematic diagram showing the morphological closing operation of the binary image of Fig. 4;
- FIG. 8 is a schematic structural diagram of a device for detecting a card provided by an embodiment of the present invention.
- FIG. 9 is a schematic structural view of the binarization unit of FIG. 8.
- FIG. 10 is a schematic structural diagram of a detecting device for a card provided by a preferred embodiment of the present invention.
- the embodiment of the invention provides a method and a device for detecting a card, which are used for detecting a card (such as a PCB card), in particular, whether the solder surface of the card enters a detection area on the conveyor.
- a card such as a PCB card
- an embodiment of the present invention provides a method for detecting a card.
- the method for detecting the card may be implemented by a detecting device of the card, and at least includes the following steps:
- the conveyor belt can continuously transport the card in a certain conveying direction, and the detecting device of the card collects an image of the card in the transportation, specifically, the
- the detection device of the card may include a camera that is mounted above the conveyor belt and acquires an image of the detection area on the conveyor belt in real time.
- the detection area is the image acquisition field of view of the camera.
- the camera in order to detect the surface property of the solder surface of the card, in order to highlight the three-dimensional information of the solder surface, it is necessary to illuminate the detection area with three-color light of different angles, and further, in order to avoid In the detection, the camera also uses a telecentric lens for shooting. These two factors will limit the camera to take pictures
- the field of view size, the image acquisition field of the camera currently detected on the solder surface is generally 250*320mm ⁇ 510*460mm, and its length and/or width may be smaller than the size of the board itself, that is, it is often required to pass local Shoot the board and shoot it.
- S102 Match the image to be tested with a preset template image to obtain a similarity between the image to be tested and the template image, where the template image is an area of the card in the detection area. An image when the ratio of the area of the detection area is a predetermined ratio.
- the template image is an image when a ratio of an area of the card in the detection area to a total area of the detection area is a predetermined ratio, wherein the predetermined ratio is a predefined value.
- a threshold value for the board to enter the detection area is determined. For example, when the detecting device of the card sets that the ratio of the area of the card to the area of the detection area is greater than or equal to one quarter, the card enters the detection area, and the The template image is an image acquired when the ratio of the area of the board to the area of the detection area is exactly one quarter.
- one quarter is only a reference parameter, which may also be set to 1/6, 1/8, 1/2 or other values according to actual needs, and the present invention No specific restrictions.
- the template image is also related to the direction of movement and initial placement of the card on the conveyor belt, and the card is The portion within the detection area should be the portion where it first enters the detection area.
- the similarity between the image to be tested and the template image may be obtained by:
- T(x, y) be the template image
- I(x, y) be the image to be tested
- T '(x', y ' ) T (x', y ') - 1 / (w ⁇ h) ⁇ ⁇ x ", y" T (x ", y")
- I'(x+x',y+y') I(x+x',y+y')-1/(w ⁇ h) ⁇ x′′,y′′ I(x+x′′,y+ y").
- x and y are the coordinates of the points on the corresponding image
- w and h are the width and height of the image, respectively.
- the ratio of the area of the detection area is exactly the preset ratio, that is, when the similarity is 1, it is the time point when the board enters the detection area for the first time.
- a preset allowable value for example, 0.01
- the board cannot be considered to have not entered the detection area, for example, slight changes in illumination or errors in mechanical structure may affect similarity. Calculation results. Therefore, when the similarity is less than a preset threshold, the detecting device of the card further calculates a binary image of the image to be tested for further judgment.
- step S103 may include:
- the HSV value of the image to be tested can be calculated by the following method:
- H the hue
- S the saturation
- V the value
- the color of the bottom surface of the soldering surface of the board can be obtained.
- the color of the bottom board is green, and the board can be obtained by the above conversion formula.
- Base plate color HSV The value of the card detecting device can store the HSV value of the color of the board bottom plate.
- the detecting device of the card compares the HSV value of each pixel of the image to be tested with the HSV value of the color of the board bottom plate, and determines whether the pixel point and the color of the board bottom layer Matching; if yes, setting the gray value of the pixel to 1 on the image to be tested, and if not, setting the gray value of the pixel to 0 on the image to be tested.
- the gray value here is a normalized gray value, that is, the gray value is 0 for all black, and the gray value is 1 for all white.
- the matching process is: when the difference between the H value of one pixel of the image to be tested and the H value of the color of the board bottom is less than a preset error, the S value of the pixel of the image to be tested The difference between the S value and the color of the board bottom plate is less than a preset error, and the difference between the V value of the pixel of the image to be tested and the V value of the color of the board bottom plate is less than a preset error.
- the pixel of the image to be tested matches the color of the board bottom plate. If at least one of the three conditions is not satisfied, the pixel of the image to be tested does not match the color of the board bottom board. .
- the specific calculation process is as follows:
- H background , S background , V background represent the HSV value of the color of the board base plate
- H test (i, j) S test (i, j)
- V test (i, j) is the image to be tested (i , j) the HSV value at the coordinates
- C is the allowable error.
- the generated binary image can be as shown in FIG. 4 .
- an outline on the binary image may be acquired, wherein the extraction of the contour may be implemented according to an existing algorithm, for example, when determining a pixel point with a gray value of 1
- the gray values of adjacent pixels are all 1, and the point is the inner point of the contour, and vice versa.
- Contour extraction is done by setting all interior points to background points.
- the detecting means of the card calculates the area of the connected area surrounded by the outline, and calculates the area of the minimum circumscribed rectangle of the connected area having the largest area.
- the detecting device of the card determines whether the ratio of the area of the circumscribed rectangle to the area of the binary image is greater than the predetermined ratio If yes, then the description The board has entered the detection area, otherwise it indicates that the board has not entered the detection area.
- the method for detecting a board provided by the embodiment of the present invention, after binarizing the image to be tested, according to the area of the minimum circumscribed rectangle of the connected area having the largest area on the binary image
- the ratio of the area of the binary image determines whether the card enters the detection area, so that it is possible to accurately determine whether the card enters the detection without requiring a high-precision mechanical motion structure. within the area.
- step S102 further includes:
- the boundary of the image to be tested is expanded, wherein the expanded portion is filled with pixels having a gray value of 0.
- FIG. 6 is a result of expanding FIG. 2, by which the error due to the positional deviation of the mechanical structure is eliminated, so that the calculation result of the similarity is more accurate. .
- the method before step S104, the method further includes:
- a morphological closing operation is performed on the binary image to perform morphological filling and noise cancellation on the binary image.
- Fig. 7 shows the binary image after the morphological closing operation, and it can be seen that most of the noise has been eliminated, thereby ensuring accurate extraction of the contour.
- an embodiment of the present invention further provides a card detecting apparatus 100, including:
- the collecting unit 10 is configured to collect an image to be tested of the detection area located on the conveyor belt.
- a similarity matching unit 20 configured to match the image to be tested with a preset template image to obtain a similarity between the image to be tested and the template image; wherein the template image is a card in the An image when the ratio of the area in the detection area to the area of the detection area is a predetermined ratio.
- the binarization unit 30 is configured to perform binarization on the image to be tested when the similarity is less than a preset threshold to obtain a binary image of the image to be tested.
- the binarization unit 30 specifically includes an HSV value calculation module 31 and a matching module. 32 and binary image generation module 33, wherein:
- the HSV value calculation module 31 is configured to: when the similarity is less than a preset threshold, calculate an HSV of each pixel of the image to be tested according to an RGB value of each pixel of the image to be tested. Value, where H is the hue, S is the saturation, and V is the value.
- the matching module 32 is configured to compare an HSV value of each pixel of the image to be tested with a HSV value of a preset color of the board bottom layer, and determine whether the pixel point and the board bottom color Matching; if yes, setting the gray value of the pixel to 1 on the image to be tested, and if not, setting the gray value of the pixel to 0 on the image to be tested.
- the S value of the pixel of the image to be tested and the board is smaller than a preset error
- the difference between the V value of the pixel of the image to be tested and the V value of the color of the bottom plate of the board is less than the preset error, and the three conditions are simultaneously established.
- the pixel of the image to be tested matches the color of the board backplane.
- the binary image generating module 33 is configured to generate a binary image after completing an alignment of the HSV value of all the pixel points of the image to be tested with the HSV value of the preset board bottom color.
- the contour extracting unit 40 is configured to extract all the contours on the binary image, calculate the area of the connected region surrounded by the contour, and obtain the area of the minimum circumscribed rectangle of the connected region having the largest area.
- the ratio calculating unit 50 is configured to determine that the card enters the detection area when a ratio of an area of the minimum circumscribed rectangle to an area of the binary image is greater than or equal to the predetermined ratio.
- the detecting device 100 for the card provided by the embodiment of the present invention binarizes the image to be tested by the binarization unit 30, and then calculates the maximum value on the binary image according to the contour extracting unit 40. Determining, by the ratio calculating unit 50, a ratio of an area of the minimum circumscribed rectangle to an area of the binary image to determine whether the card enters the detection area, thereby determining an area of the minimum circumscribed rectangle of the connected area of the area. In the case where a high-precision mechanical motion structure is not required, it is also possible to accurately judge whether or not the board enters the detection area.
- the detecting device 100 of the card further comprises:
- the expansion unit 60 is configured to expand a boundary of the image to be tested, wherein the extended portion is filled with pixels with a gray value of 0.
- FIG. 6 is a result of expanding FIG. 2, by which the error due to the positional deviation of the mechanical structure is eliminated, so that the calculation result of the similarity is more accurate. .
- the detecting device 100 of the card further comprises:
- the morphological closing unit 70 is configured to perform a morphological closing operation on the binary image to perform morphological filling and noise elimination on the binary image.
- Fig. 7 shows the binary image after the morphological closing operation, and it can be seen that most of the noise has been eliminated, thereby ensuring accurate extraction of the contour.
- the storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).
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Abstract
一种板卡的检测方法,包括:采集位于传送带上的检测区域的待测图像(S101);将所述待测图像与预置的模板图像进行匹配,获得所述待测图像与所述模板图像的相似度(S102);当所述相似度小于预设的阈值时,对所述待测图像进行二值化,获得所述待测图像的二值图像(S103);提取所述二值图像上的所有轮廓,计算由所述轮廓围起来的连通区域的面积,并获得具有最大面积的连通区域的最小外接矩形的面积(S104);当所述最小外接矩形的面积与所述二值图像的面积的比大于等于所述预定比例值时,确定所述板卡进入检测区域(S105)。还提供一种板卡的检测装置,本检测方法及装置可准确的判断板卡是否进入到检测区域。
Description
本发明涉及自动光学检测领域,具体是一种板卡的检测方法及装置。
自动光学检测是工业制作过程的必要环节,其原理是通过光学成像方式取得成品的表面状态,以影像处理来检测成品上的异物或表面瑕疵等。其中,确定成品是否进入到检测区域是自动光学检测的关键步骤。
PCB板卡在检测其焊锡面的进入检测中,需要利用不同角度的三色光照明,以凸显焊锡的三维信息;同时,为了避免视差带来的影响,在检测中,通常还会采用远心镜头来拍摄焊锡面的图像。以上两个因素,会限制摄像机拍照的视野大小,目前焊锡面检测的图像采集视野一般为250*320mm~510*460mm,小于板卡本身的面积,也即是说,需要通过局部拍摄板卡的方法进行拍摄。
现有技术中,在对板卡的焊锡面进行进入检测时,主要通过机械结构来提供板卡进入摄像机视野的时间与坐标。但是这种方法,极大的依赖于机械运动结构的精度,而高精度的机械运动结构,往往也意味着高成本和更多的机械维护工作,不利于降低检测成本。
发明内容
针对上述问题,本发明的目的在于提供一种板卡的检测方法及装置,在不需要高精度的结构的前提下,也可以准确的检测到板卡是否进入到检测区域。
本发明提供了一种板卡的检测方法,包括如下步骤:
采集位于传送带上的检测区域的待测图像;
将所述待测图像与预置的模板图像进行匹配,获得所述待测图像与所述模板图像的相似度;其中,所述模板图像为板卡在所述检测区域内的面积与所述检测区域的面积的比为预定比值时的图像;
当所述相似度小于预设的阈值时,对所述待测图像进行二值化,获得所述待测图像的二值图像;
提取所述二值图像上的所有轮廓,计算由所述轮廓围起来的连通区域的面积,并获得具有最大面积的连通区域的最小外接矩形的面积;
当所述最小外接矩形的面积与所述二值图像的面积的比大于等于所述预定比例值时,确定所述板卡进入检测区域。
优选地,在将所述待测图像与预置的模板图像进行匹配,获得所述待测图像与所述模板图像的相似度之前,还包括:
对所述待测图像的边界进行扩展,其中,扩展的部分用灰度值为0的像素点进行填充。
优选地,所述当所述相似度小于预设的阈值时,对所述待测图像进行二值化,获得所述待测图像的二值图像,具体包括:
当所述相似度小于预设的阈值时,根据所述待测图像的每个像素点的RGB值计算获得所述待测图像的每个像素点的HSV值,其中,H为色调,S为饱和度,V为数值;
将所述待测图像的每个像素点的HSV值与预设的板卡底板颜色的HSV值进行比对,判断所述像素点是否与所述板卡底板颜色相匹配;若是,则在所述待测图像上将所述像素点的灰度值设置为1,若否,则在所述待测图像上将所述像素点的灰度值设置为0;其中,当所述待测图像的一个像素点的H值与所述板卡底板颜色的H值的差小于预设的误差,所述待测图像的该像素点的S值与所述板卡底板颜色的S值的差小于预设的误差,所述待测图像的该像素点的V值与所述板卡底板颜色的V值的差小于预设的误差三个条件同时成立时,所述待测图像的该像素点与所述板卡底板颜色相匹配;
在完成所述待测图像的所有像素点的HSV值与预设的板卡底板颜色的HSV值的比对后,生成二值图像。
优选地,在提取所述二值图像上的所有轮廓,计算由所述轮廓围起来的连通区域的面积,并获得具有最大面积的连通区域的最小外接矩形的面积之前,还包括:
对所述二值图像进行形态学闭运算,以对所述二值图像进行形态学填充及噪声消除。
优选地,当所述相似度与1的差的绝对值小于预设的允许值时,则确定所述待测图像为所述板卡第一次进入所述检测区域的图像。
优选地,所述预定比值为1/4。
本发明还提供一种板卡的检测装置,包括:
采集单元,用于采集位于传送带上的检测区域的待测图像;
相似度匹配单元,用于将所述待测图像与预置的模板图像进行匹配,获得所述待测图像与所述模板图像的相似度;其中,所述模板图像为板卡在所述检测区域内的面积与所述检测区域的面积的比为预定比值时的图像;
二值化单元,用于当所述相似度小于预设的阈值时,对所述待测图像进行二值化,获得所述待测图像的二值图像;
轮廓提取单元,用于提取所述二值图像上的所有轮廓,计算由所述轮廓围起来的连通区域的面积,并获得具有最大面积的连通区域的最小外接矩形的面积;
比值计算单元,用于当所述最小外接矩形的面积与所述二值图像的面积的比大于等于所述预定比例值时,确定所述板卡进入检测区域。
优选地,还包括:
扩展单元,用于对所述待测图像的边界进行扩展,其中,扩展的部分用灰度值为0的像素点进行填充。
优选地,所述二值化单元具体包括:
HSV值计算模块,用于当所述相似度小于预设的阈值时,根据所述待测图像的每个像素点的RGB值计算获得所述待测图像的每个像素点的HSV值,其中,H为色调,S为饱和度,V为数值;
匹配模块,用于将所述待测图像的每个像素点的HSV值与预设的板卡底板颜色的HSV值进行比对,判断所述像素点是否与所述板卡底板颜色相匹配;若是,则在所述待测图像上将所述像素点的灰度值设置为1,若否,则在所述待测图像上将所述像素点的灰度值设置为0;其中,当所述待测图像的一个像素点的H值与所述板卡底板颜色的H值的差小于预设的误差,所述待测图像的该像素点的S值与所述板卡底板颜色的S值的差小于预设的误差,所述待测图像的该像素点的V值与所述板卡底板颜色的V值的差小于预设的误差三个条件同时成立时,所述待测图像的该像素点与所述板卡底板颜色相匹配;
二值图像生成模块,用于在完成所述待测图像的所有像素点的HSV值与预设的板卡底板颜色的HSV值的比对后,生成二值图像。
优选地,还包括:
形态学闭运算单元,用于对所述二值图像进行形态学闭运算,以对所述二值图像进行形态学填充及噪声消除。
本发明实施例提供的板卡的检测方法及装置,通过将所述待测图像进行二值化后,再根据二值图像上的具有最大面积的连通区域的最小外接矩形的面积与所述二值图像的面积的比来确定所述板卡是否进入到所述检测区域,从而在不需要高精度的机械运动结构的情况下,也能准确的判断所述板卡是否进入到检测区域内。
为了更清楚地说明本发明的技术方案,下面将对实施方式中所需要使用的附图作简单地介绍,显而易见地,下面描述中的附图仅仅是本发明的一些实施方式,对于本领域普通技术人员来讲,在不付出创造性劳动的前提下,还可以根据这些附图获得其他的附图。
图1是本发明实施例提供的板卡的检测方法的流程示意图。
图2是本发明实施例提供的待测图像的示意图。
图3(a)至图3(a)是本发明实施例提供的模板图像的示意图。
图4是本发明实施例提供的二值图像的示意图。
图5是在二值图像上确定出具有最大面积的连通区域的最小外接矩形的示意图。
图6是对图2的待测图像进行扩展的示意图。
图7是对图4的二值图像进行形态学闭运算后的示意图。
图8是本发明实施例提供的板卡的检测装置的结构示意图。
图9是图8的二值化单元的结构示意图。
图10本发明优选实施例提供的板卡的检测装置的结构示意图。
下面将结合本发明实施例中的附图,对本发明实施例中的技术方案进行清楚、完整地描述,显然,所描述的实施例仅仅是本发明一部分实施例,而不是全部的实施例。基于本发明中的实施例,本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例,都属于本发明保护的范围。
本发明实施例提供一种板卡的检测方法及装置,用于检测板卡(如PCB板卡),特别是板卡的焊锡面是否进入到位于传送带上的检测区域。以下分别进行详细的描述。
请参阅图1,本发明实施例提供一种板卡的检测方法,所述板卡的检测方法可由板卡的检测装置来实施,其至少包括如下步骤:
S101,采集位于传送带上的检测区域的待测图像。
如图2所示,在本发明实施例中,所述传送带可沿一定的传送方向连续不断地输送板卡,所述板卡的检测装置采集输送中的板卡的图像,具体为,所述板卡的检测装置可包括摄像头,所述摄像头架设于传送带上方,并实时采集所述传送带上的检测区域的图像。其中,所述检测区域即为所述摄像头的图像采集视野。
在本发明实施例中,由于是为了检测所述板卡的焊锡面的表面性质,因而为了凸显焊锡面的三维信息,还需要对所述检测区域利用不同角度的三色光照明,此外,为了避免视差带来的影响,在检测中,所述摄像头还采用远心镜头进行拍摄。这两个因素会限制摄像头拍照
的视野大小,目前在焊锡面检测的摄像头的图像采集视野一般为250*320mm~510*460mm,其长和/或宽可能会小于所述板卡本身的尺寸,也就是说,往往需要通过局部拍摄板卡的方法进行拍摄及检测。
S102,将所述待测图像与预置的模板图像进行匹配,获得所述待测图像与所述模板图像的相似度;其中,所述模板图像为板卡在所述检测区域内的面积与所述检测区域的面积的比为预定比值时的图像。
在本发明实施例中,所述模板图像为板卡在所述检测区域内的面积与所述检测区域的总面积的比为预定比值时的图像,其中,所述预定比值为预先定义好的确定所述板卡进入到所述检测区域的临界值。例如,当所述板卡的检测装置设定当所述板卡的面积与所述检测区域的面积的比值大于等于四分之一时,所述板卡就进入到所述检测区域,则所述模板图像即为所述板卡的面积与所述检测区域的面积的比值正好为四分之一时采集的图像。
当然,应该理解是在,在本发明实施例中,四分之一仅是一个参考的参数,其还可根据实际需要设置为1/6,1/8,1/2或其他数值,本发明不做具体限定。
此外,如图3(a)至图3(c)所示,还应该理解的是,所述模板图像还与所述板卡在传送带上的运动方向和初始放置位置有关,且所述板卡在所述检测区域内的部分应该是其先进入所述检测区域的部分。
在本发明实施例中,可通过如下方法来获得所述待测图像与所述模板图像的相似度,具体地:
设T(x,y)为模板图像,I(x,y)为待测图像,首先通过下式分别计算所述模板图像与所述待测图像减去其均值的图像:
T′(x′,y′)=T(x′,y′)-1/(w·h)·Σx″,y″T(x″,y″)
I′(x+x′,y+y′)=I(x+x′,y+y′)-1/(w·h)·Σx″,y″I(x+x″,y+y″)。
其中,x和y为在对应图像上的点的坐标,w和h分别为图像的宽度和高度。
然后再通过下式计算相似度:
当然,应该理解的是,还可以通过其他算法来计算获得所述待测图像与所述模板图像的相似度,本发明不做具体限定。
S103,当所述相似度小于预设的阈值时,对所述待测图像进行二值化,获得所述待测图像的二值图像。
在本发明实施例中,若相似度等于1,则说明此时板卡在所述检测区域内的面积与所述
检测区域的面积的比值正好为所述预设比值,也就是说相似度为1的时候,即为所述板卡第一次进入所述检测区域的时间点。当然,由于很难保证能够得到相似度为1的情况,从不那么严格的角度出发,所述相似度与1的差的绝对值小于预设的允许值(如0.01)时,都可以认为其是所述板卡第一次进入所述检测区域的时间点。
然而,即使所述相似度小于或等于所述预设的阈值,也不能认为所述板卡还未进入到所述检测区域,例如,光照的细微变化或机械结构的误差都可能影响到相似度的计算结果。因此,当所述相似度小于预设的阈值时,所述板卡的检测装置还要计算所述待测图像的二值图像,以做进一步的判断。
具体地,步骤S103可包括:
S1031,当所述相似度小于预设的阈值时,根据所述待测图像的每个像素点的RGB值计算获得所述待测图像的每个像素点的HSV值,其中,H为色调,S为饱和度,V为数值。
其中,可通过如下方法来计算获得所述待测图像的HSV值:
将所述待测图像上的每个像素点的RGB值转换为HSV值,其转换公式如下式所示:。
V=Cmax
如此,就获得了所述待测图像上的每个像素点的HSV值,其中,H为色调,S为饱和度,V为数值。
S1032,将所述待测图像的每个像素点的HSV值与预设的板卡底板颜色的HSV值进行比对,判断所述像素点是否与所述板卡底板颜色相匹配。
在本发明实施例中,在制作板卡的标准版式的时候,可以得到板卡的焊锡面的底板的颜色,比如对于绿色板卡,底板颜色即为绿色,通过上述的转换公式可获得板卡底板颜色的HSV
值,所述板卡的检测装置可存储所述板卡底板颜色的HSV值。然后,所述板卡的检测装置将所述待测图像的每个像素点的HSV值与所述板卡底板颜色的HSV值进行比对,判断所述像素点是否与所述板卡底板颜色相匹配;若是,则在所述待测图像上将所述像素点的灰度值设置为1,若否,则在所述待测图像上将所述像素点的灰度值设置为0。需要说明的是,这里的灰度值为归一化后的灰度值,即灰度值为0代表全黑色,而灰度值为1代表全白色。
其中,匹配的过程为:当所述待测图像的一个像素点的H值与所述板卡底板颜色的H值的差小于预设的误差,所述待测图像的该像素点的S值与所述板卡底板颜色的S值的差小于预设的误差,所述待测图像的该像素点的V值与所述板卡底板颜色的V值的差小于预设的误差三个条件同时成立时,所述待测图像的该像素点与所述板卡底板颜色相匹配,若三个条件有至少一个不成立,则述待测图像的该像素点与所述板卡底板颜色不匹配。具体计算过程如下式所示:
其中Hbackground、Sbackground、Vbackground表示板卡底板颜色的HSV值,Htest(i,j)、Stest(i,j)、Vtest(i,j)为所述待测图像在(i,j)坐标处的HSV值,C为允许的误差。
S1033,在完成所述待测图像的所有像素点的HSV值与预设的板卡底板颜色的HSV值的比对后,生成二值图像。
其中,生成的二值图像可如图4所示。
S104,提取所述二值图像上的所有轮廓,计算由所述轮廓围起来的连通区域的面积,并获得具有最大面积的连通区域的最小外接矩形的面积。
具体的,在生成所述二值图像后,可获取所述二值图像上的轮廓,其中,轮廓的提取可根据现有的算法实现,例如,当判断灰度值为1的像素点的8个相邻像素点的灰度值全部为1,则该点为轮廓的内部点,反之为轮廓点。将所有内部点置为背景点,就完成了轮廓提取。
如图5所示,在提取出轮廓后,所述板卡的检测装置计算由所述轮廓围起来的连通区域的面积,并计算具有最大面积的连通区域的最小外接矩形的面积。
S105,当所述最小外接矩形的面积与所述二值图像的面积的比大于等于所述预定比例值时,确定所述板卡进入检测区域。
在本发明实施例中,在获得所述最小外接矩形的面积后,所述板卡的检测装置判断所述外接矩形的面积与所述二值图像的面积的比是否大于所述预定比例值时,若是,则说明所述
板卡已经进入到检测区域里了,否则,则表明所述板卡还未进入到所述检测区域。
综上所述,本发明实施例提供的板卡的检测方法,通过将所述待测图像进行二值化后,再根据二值图像上的具有最大面积的连通区域的最小外接矩形的面积与所述二值图像的面积的比来确定所述板卡是否进入到所述检测区域,从而在不需要高精度的机械运动结构的情况下,也能准确的判断所述板卡是否进入到检测区域内。
为了便于对本发明的理解,下面对本发明的一些优选实施例做更进一步的描述。
第一个优选实施例:
由于机械结构本身具有偏移误差,因而会导致所述板卡在所述传送带上运动的时候,与实际的预想有偏差,从而摄像头拍摄到的检测图像与所述模板图像拍摄得到的板卡位置存在位置偏移。为了消除这种位置偏移带来的误差,本优选实施在步骤S102之前,还包括:
对所述待测图像的边界进行扩展,其中,扩展的部分用灰度值为0的像素点进行填充。
具体地,如图6所示,图6为对图2进行扩展后的结果,通过这种扩展,消除了由于机械结构的位置偏移带来的误差,使得所述相似度的计算结果更准确。
第二个优选实施例:
如图5所示,在进行二值化的时候,会有很多噪声,这些噪声会影响轮廓的提取,因此,在提取轮廓前,需先消除这些噪声。
为此,在本优选实施例中,在步骤S104之前,还包括:
对所述二值图像进行形态学闭运算,以对所述二值图像进行形态学填充及噪声消除。
如图7所示,图7为经过形态学闭运算后的二值图像,可见大部分的噪声均已被消除,从而保证了轮廓的准确提取。
请参阅图8,本发明实施例还提供一种板卡的检测装置100,其包括:
采集单元10,用于采集位于传送带上的检测区域的待测图像。
相似度匹配单元20,用于将所述待测图像与预置的模板图像进行匹配,获得所述待测图像与所述模板图像的相似度;其中,所述模板图像为板卡在所述检测区域内的面积与所述检测区域的面积的比为预定比值时的图像。
二值化单元30,用于当所述相似度小于预设的阈值时,对所述待测图像进行二值化,获得所述待测图像的二值图像。
具体地,请一并参阅图9,所述二值化单元30具体包括HSV值计算模块31、匹配模块
32及二值图像生成模块33,其中:
所述HSV值计算模块31,用于当所述相似度小于预设的阈值时,根据所述待测图像的每个像素点的RGB值计算获得所述待测图像的每个像素点的HSV值,其中,H为色调,S为饱和度,V为数值。
所述匹配模块32,用于将所述待测图像的每个像素点的HSV值与预设的板卡底板颜色的HSV值进行比对,判断所述像素点是否与所述板卡底板颜色相匹配;若是,则在所述待测图像上将所述像素点的灰度值设置为1,若否,则在所述待测图像上将所述像素点的灰度值设置为0。
其中,当所述待测图像的一个像素点的H值与所述板卡底板颜色的H值的差小于预设的误差,所述待测图像的该像素点的S值与所述板卡底板颜色的S值的差小于预设的误差,所述待测图像的该像素点的V值与所述板卡底板颜色的V值的差小于预设的误差三个条件同时成立时,所述待测图像的该像素点与所述板卡底板颜色相匹配。
所述二值图像生成模块33,用于在完成所述待测图像的所有像素点的HSV值与预设的板卡底板颜色的HSV值的比对后,生成二值图像。
轮廓提取单元40,用于提取所述二值图像上的所有轮廓,计算由所述轮廓围起来的连通区域的面积,并获得具有最大面积的连通区域的最小外接矩形的面积。
比值计算单元50,用于当所述最小外接矩形的面积与所述二值图像的面积的比大于等于所述预定比例值时,确定所述板卡进入检测区域。
综上所述,本发明实施例提供的板卡的检测装置100,通过二值化单元30将所述待测图像进行二值化后,再根据轮廓提取单元40计算二值图像上的具有最大面积的连通区域的最小外接矩形的面积,由比值计算单元50计算所述最小外接矩形的面积与所述二值图像的面积的比来确定所述板卡是否进入到所述检测区域,从而在不需要高精度的机械运动结构的情况下,也能准确的判断所述板卡是否进入到检测区域内。
请一并参阅图9,优选地,板卡的检测装置100还包括:
扩展单元60,用于对所述待测图像的边界进行扩展,其中,扩展的部分用灰度值为0的像素点进行填充。
具体地,如图6所示,图6为对图2进行扩展后的结果,通过这种扩展,消除了由于机械结构的位置偏移带来的误差,使得所述相似度的计算结果更准确。
优选地,板卡的检测装置100还包括:
形态学闭运算单元70,用于对所述二值图像进行形态学闭运算,以对所述二值图像进行形态学填充及噪声消除。
如图7所示,图7为经过形态学闭运算后的二值图像,可见大部分的噪声均已被消除,从而保证了轮廓的准确提取。
以上所揭露的仅为本发明一种较佳实施例而已,当然不能以此来限定本发明之权利范围,本领域普通技术人员可以理解实现上述实施例的全部或部分流程,并依本发明权利要求所作的等同变化,仍属于发明所涵盖的范围。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程,是可以通过计算机程序来指令相关的硬件来完成,所述的程序可存储于一计算机可读取存储介质中,该程序在执行时,可包括如上述各方法的实施例的流程。其中,所述的存储介质可为磁碟、光盘、只读存储记忆体(Read-Only Memory,ROM)或随机存储记忆体(Random Access Memory,RAM)等。
Claims (10)
- 一种板卡的检测方法,其特征在于,包括如下步骤:采集位于传送带上的检测区域的待测图像;将所述待测图像与预置的模板图像进行匹配,获得所述待测图像与所述模板图像的相似度;其中,所述模板图像为板卡在所述检测区域内的面积与所述检测区域的面积的比为预定比值时的图像;当所述相似度小于预设的阈值时,对所述待测图像进行二值化,获得所述待测图像的二值图像;提取所述二值图像上的所有轮廓,计算由所述轮廓围起来的连通区域的面积,并获得具有最大面积的连通区域的最小外接矩形的面积;当所述最小外接矩形的面积与所述二值图像的面积的比大于等于所述预定比例值时,确定所述板卡进入检测区域。
- 根据权利要求1所述的板卡的检测方法,其特征在于,在将所述待测图像与预置的模板图像进行匹配,获得所述待测图像与所述模板图像的相似度之前,还包括:对所述待测图像的边界进行扩展,其中,扩展的部分用灰度值为0的像素点进行填充。
- 根据权利要求1所述的板卡的检测方法,其特征在于,所述当所述相似度小于预设的阈值时,对所述待测图像进行二值化,获得所述待测图像的二值图像,具体包括:当所述相似度小于预设的阈值时,根据所述待测图像的每个像素点的RGB值计算获得所述待测图像的每个像素点的HSV值,其中,H为色调,S为饱和度,V为数值;将所述待测图像的每个像素点的HSV值与预设的板卡底板颜色的HSV值进行比对,判断所述像素点是否与所述板卡底板颜色相匹配;若是,则在所述待测图像上将所述像素点的灰度值设置为1,若否,则在所述待测图像上将所述像素点的灰度值设置为0;其中,当所述待测图像的一个像素点的H值与所述板卡底板颜色的H值的差小于预设的误差,所述待测图像的该像素点的S值与所述板卡底板颜色的S值的差小于预设的误差,所述待测图像的该像素点的V值与所述板卡底板颜色的V值的差小于预设的误差三个条件同时成立时,所述待测图像的该像素点与所述板卡底板颜色相匹配;在完成所述待测图像的所有像素点的HSV值与预设的板卡底板颜色的HSV值的比对后,生成二值图像。
- 根据权利要求1所述的板卡的检测方法,其特征在于,在提取所述二值图像上的所有轮廓,计算由所述轮廓围起来的连通区域的面积,并获得具有最大面积的连通区域的最小外接矩形的面积之前,还包括:对所述二值图像进行形态学闭运算,以对所述二值图像进行形态学填充及噪声消除。
- 根据权利要求1所述的板卡的检测方法,其特征在于,当所述相似度与1的差的绝对值小于预设的允许值时,则确定所述待测图像为所述板卡第一次进入所述检测区域的图像。
- 根据权利要求1至5任意一项所述的板卡的检测方法,其特征在于,所述预定比值为1/4。
- 一种板卡的检测装置,其特征在于,包括:采集单元,用于采集位于传送带上的检测区域的待测图像;相似度匹配单元,用于将所述待测图像与预置的模板图像进行匹配,获得所述待测图像与所述模板图像的相似度;其中,所述模板图像为板卡在所述检测区域内的面积与所述检测区域的面积的比为预定比值时的图像;二值化单元,用于当所述相似度小于预设的阈值时,对所述待测图像进行二值化,获得所述待测图像的二值图像;轮廓提取单元,用于提取所述二值图像上的所有轮廓,计算由所述轮廓围起来的连通区域的面积,并获得具有最大面积的连通区域的最小外接矩形的面积;比值计算单元,用于当所述最小外接矩形的面积与所述二值图像的面积的比大于等于所述预定比例值时,确定所述板卡进入检测区域。
- 根据权利要求7所述的板卡的检测装置,其特征在于,还包括:扩展单元,用于对所述待测图像的边界进行扩展,其中,扩展的部分用灰度值为0的像素点进行填充。
- 根据权利要求7所述的板卡的检测装置,其特征在于,所述二值化单元具体包括:HSV值计算模块,用于当所述相似度小于预设的阈值时,根据所述待测图像的每个像素点的RGB值计算获得所述待测图像的每个像素点的HSV值,其中,H为色调,S为饱和度,V为数值;匹配模块,用于将所述待测图像的每个像素点的HSV值与预设的板卡底板颜色的HSV值进行比对,判断所述像素点是否与所述板卡底板颜色相匹配;若是,则在所述待测图像上将所述像素点的灰度值设置为1,若否,则在所述待测图像上将所述像素点的灰度值设置为0;其中,当所述待测图像的一个像素点的H值与所述板卡底板颜色的H值的差小于预设的误差,所述待测图像的该像素点的S值与所述板卡底板颜色的S值的差小于预设的误差,所述待测图像的该像素点的V值与所述板卡底板颜色的V值的差小于预设的误差三个条件同时成立时,所述待测图像的该像素点与所述板卡底板颜色相匹配;二值图像生成模块,用于在完成所述待测图像的所有像素点的HSV值与预设的板卡底板颜色的HSV值的比对后,生成二值图像。
- 根据权利要求7所述的板卡的检测装置,其特征在于,还包括:形态学闭运算单元,用于对所述二值图像进行形态学闭运算,以对所述二值图像进行形态学填充及噪声消除。
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