Note: The number of iterations is the number of times erosion or dilatation operation will be applied. we use 4-connexity). The computed response is stored in the destination image at the same location . Imgproc.morphologyEx(input_image, output_image, Imgproc.MORPH_HITMISS, kernel); Imgproc.resize(output_image, output_image. Imgproc.morphologyEx (Showing top 10 results out of 315) org.opencv.imgproc Imgproc morphologyEx c++. First we use imread () to read the input file and cvtColor () to convert the input image into gray scale. So we dilate it. Negative values mean that the anchor is at the kernel center. In this tutorial you will learn how to find a given configuration or pattern in a binary image by using the Hit-or-Miss transform (also known as Hit-and-Miss transform). A way of adding images is through blending them so that they both can be visible together. anchor position within the element. dst: It is the output image. It is of two types: morphologyEx (src, dst, op, kernel, anchor, iterations, borderType, borderValue). OpenCV ,OpenCV OpenCV,OpenCV2OpenCV3 . In the previous tutorial we covered two basic Morphology operations: Erosion Dilation. Hit-or-Miss theory Morphological operators process images based on their shape. C++ Kinect for Windows v2 c++ opencv opencvrgb 1.import cv2 #opencvBGRimport numpy as npimport matplotlib.pyplot as plt#MatplotlibRGB%matplotlib inline img=c. The computed response is stored in the destination image at the same location . Here are the examples of the csharp api class OpenCvSharp.Cv2.MorphologyEx(OpenCvSharp.InputArray, OpenCvSharp.OutputArray, OpenCvSharp.MorphTypes, OpenCvSharp.InputArray, System.Nullable, int, OpenCvSharp.BorderTypes, System.Nullable) taken from open source projects. Note that only the shape of a cross-shaped element depends on the anchor position. op: Type of morphological operation. The Hit-or-Miss transformation is useful to find patterns in binary images. This operator is used to remove small holes from the image. 7.cv2.morphologyExcv2.MORPH_OPENcv2.morphologyExcv2.MORPH_CLOSE . morphologyEx (src, dst, op, kernel, anchor, iterations, borderType, borderValue) Parameters: src: It is the input image. Morphological . op: Type of morphological operation. These operators apply one or more structuring elements to an input image to obtain the output image. Morphological transformations are some simple operations based on the image shape. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. It is also useful in joining broken parts of an object. Contour detection and filtering The function cv.morphologyEx can perform advanced morphological transformations using an erosion and dilation as basic operations. Open CV provides 3 shapes for kernel rectangular, cross . It can be created using. connectedComponents4. Structuring Element: A structuring element is a shape used to interact with a given image. The following are 30 code examples of cv2.morphologyEx () . We manually created a structuring elements in the previous examples with help of cv.Mat.ones. asking for an explaining of morphologyex function !. The gradient is defined as the difference between the Dilation and Erosion of an image. If you would like to change your settings or withdraw consent at any time, the link to do so is in our privacy policy accessible from our home page. By voting up you can indicate which examples are most useful and appropriate. Therefore you can use the OpenCV library even for your commercial applications. The default value [1,1] means that the anchor is at the center. In this program, we will perform the Blackhat operation on an image using OpenCV. Table of Contents Recipe Objective: What is the Morphological gradient of an image in OpenCV? Thinning of set A by SE B can be expressed in terms of hit-or-miss transform as This means we remove all those pixels whose neighborhood exactly matches the pixels in the SE. Morphological transformations are some simple operations based on the image shape. OPENCVMatgetPerspectiveTransform( cons point2fsrc [], const Point2fdst []) src- dst- . By using our site, you According to the documentation of morphologyEx, kernel is a Structuring element, and not the size of the kernel. 5. But the problem appears when I apply it to other images with the same structure output is distorted. structuring element. morphologyEx (thresh, cv2. morphologyex. The input image contains numbers written with intensity (grayscale value) equal to the number itself. The correct syntax is passing 3x11 NumPy a array of ones (and uint8 type): Some of our partners may process your data as a part of their legitimate business interest without asking for consent. position of the anchor within the element; default value new, border value in case of a constant border, source image. Yes! These images can be added and used together for further analysis. So for this purpose, OpenCV has a function, cv.getStructuringElement(). It is just opposite of erosion. Normally, the functions support multi-channel arrays, in which case every channel is processed independently. Manage SettingsContinue with Recommended Cookies. OpenCV . are called morphological transformations. Install OpenCV on Ubuntu Input Image In the following examples, we will use this image as input. morphologyEx (src,op,kernel,dst = None,anchor = None,iterations = None,borderType = None,borderValue = None) erode () dilate () opening operation (): close operation (): In this article, another operator is elaborated called closing which is just the reverse of Opening and applies dilation followed by. You just pass the shape and size of the kernel, you get the desired kernel. In the previous tutorial we covered two basic Morphology operations: Erosion Dilation. Now, let's discuss how to implement this using OpenCV-Python. It takes an image, type of the operation, kernel, anchor position, iterations, borderType . The consent submitted will only be used for data processing originating from this website. . It needs two inputs, one is our original image, second one is called structuring element or kernel which decides the nature of operation. kernel: Structuring element used for Closing. so how can i pass a numpy array as an input to c++ function, than convert that array to Mat (opencv) in c++ and do the operations in c++ and return that Mat back to python script. As you can see, it is as simple as using the function morphologyEx() with the operation type MORPH_HITMISS and the chosen kernel. Here you can find the output results of applying different kernels to the same input image used before: Structuring elements (kernels). OpenCV is an open source C++ library for image processing and computer vision, originally developed by Intel, later supported by Willow Garage and and is now maintained by Itseez. For example, the pixel intensity of the number '200' is 200, and the intensity of the number '32' is 32. 2matlabel. Another approach is to use OpenCV cv2.morphologyEx () function with cv2.MORPH_GRADIENT flag as discussed in the previous blog. Similarly, we have a closing operation which is an inverse of the opening. HuangCongQing / OpenCV Public Notifications Fork 11 Star 59 Code Issues Pull requests Actions Projects Security Insights master OpenCV/01-/template-matching-ocr/ocr_template_match.py Go to file HuangCongQing update Latest commit ed01d70 on Jan 24, 2021 History 1 contributor 203 lines (170 sloc) 7.03 KB Raw Blame They process objects in the input image based on characteristics of its shape, which are encoded in the structuring element. OpenCV library in Python helps us in adding two images. For this, we will use the function cv2.morphologyEx (). The morphologyEx () of the method of the class Imgproc is used to perform these operations on a given image. dst: It is the output image. Every pixel inside the Gradient image represents the contrast intensity in the neighborhood of a pixel. Use the OpenCV function cv::morphologyEx to apply Morphological Transformation such as: Opening Closing Morphological Gradient Top Hat Black Hat Theory Note The explanation below belongs to the book Learning OpenCV by Bradski and Kaehler. Morphological operators often take a binary image and a structuring element as input and combine them using a set operator (intersection, union, inclusion, complement). void morphologyEx ( InputArray src, OutputArray dst, int op, InputArray kernel, Point anchor=Point (-1,-1), int iterations=1, int borderType=BORDER_CONSTANT, const Scalar& borderValue=morphologyDefaultBorderValue () ); a newbie so THANKS in advance for your any reply or comment!. Prev Tutorial: More Morphology Transformations, Next Tutorial: Extract horizontal and vertical lines by using morphological operations. It is the difference between the closing of the input image and input image. In case of morphological operations, it is the minimum or maximum values, and so on. OutputArraydst. We will use the morphologyEx (image, cv2.MORPH_BLACKHAT, kernel) function.Original ImageAlgorithmStep 1: Import cv2. A-143, 9th Floor, Sovereign Corporate Tower, We use cookies to ensure you have the best browsing experience on our website. It is normally performed on binary images. Morphological operations based on OpenCV are as follows: Erosion Dilation Opening Closing Morphological Gradient Top hat Black hat Gradient operator is given the expression: Below is the C++ program to demonstrate the Gradient Morphological Operation: C++ Programming Foundation- Self Paced Course, Data Structures & Algorithms- Self Paced Course, Opening | Morphological Transformations in OpenCV in C++, Erosion and Dilation | Morphological Transformations in OpenCV in C++, Closing | Morphological Transformations in OpenCV in C++, Python | Morphological Operations in Image Processing (Gradient) | Set-3, Difference between Batch Gradient Descent and Stochastic Gradient Descent, Python | Morphological Operations in Image Processing (Opening) | Set-1, Python | Morphological Operations in Image Processing (Closing) | Set-2, Image segmentation using Morphological operations in Python, LightGBM (Light Gradient Boosting Machine). Following is the syntax of this method morphologyEx (src, dst, op, kernel) This method accepts the following parameters src An object of the class Mat representing the source (input) image. Before finding contours or boundaries of the image, we first find edges of the image. It means that the output image will be of the same size as the input image. Two basic morphological operators are Erosion and Dilation. XY . It takes the desired shape and the size of the kernel. kernel: Structuring element used for Closing. A pixel in the original image (either 1 or 0) will be considered 1 only if all the pixels under the kernel is 1, otherwise it is eroded (made to zero). 144. It helps to reduce the internal noise present inside an image. The cv2.morphologyEx() is used to perform compound morphological operations. We can use morphological operations to increase the size of objects in images as well as decrease them. 1connectedComponentslabelMat labels. We use the function: cv.morphologyEx (src, dst, op, kernel, anchor = new cv.Point(-1, -1), iterations = 1, borderType = cv.BORDER_CONSTANT, borderValue = cv.morphologyDefaultBorderValue()). Opening operation is erosion operation followed by dilation. Erode image \(A\) with structuring element \(B_1\). The rest of pixels in the neighbourhood can be of any kind, we don't care about them. OpenCV . OpenCV has an in-built function to erode an image specifying the kernel size. Two basic morphological operators are Erosion and Dilation. Both of these approaches are shown below. Working of morphologyEx () function in OpenCV is as follows: The simple operations performed on the images based on the shape of the images to remove noise from the image, to remove small holes in the foreground objects in the image, etc. If not then please go to below url to install it and then you can come back to this post.] It is useful in removing noise, as we explained above. Program: Erode operation . Normally, the functions support multi-channel arrays, in which case every channel is processed independently. destination image of the same size and type as source image. ins.style.display='block';ins.style.minWidth=container.attributes.ezaw.value+'px';ins.style.width='100%';ins.style.height=container.attributes.ezah.value+'px';container.appendChild(ins);(adsbygoogle=window.adsbygoogle||[]).push({});window.ezoSTPixelAdd(slotId,'stat_source_id',44);window.ezoSTPixelAdd(slotId,'adsensetype',1);var lo=new MutationObserver(window.ezaslEvent);lo.observe(document.getElementById(slotId+'-asloaded'),{attributes:true}); OpenCvSharp.Cv2.MorphologyEx(OpenCvSharp.InputArray, OpenCvSharp.OutputArray, OpenCvSharp.MorphTypes, OpenCvSharp.InputArray, System.Nullable, int, OpenCvSharp.BorderTypes, System.Nullable). We will use the OpenCV function morphologyEx() . int . More specifically, we apply morphological operations to shapes and structures inside of images. One approach is to use OpenCV cv2.dilate () and cv2.erode () functions and then subtract these two. Step 2: Converting Grayscale image to binary image. Now, let's apply this kernel to an input image: You can see that the pattern is found in just one location within the image. OpenCVC++& 1 . After that, we apply findContours () to find the contours of . In particular, it finds those pixels whose neighbourhood matches the shape of a first structuring element \(B_1\) while not matching the shape of a second structuring element \(B_2\) at the same time. During dilation, additional pixels are added to the image boundaries. This forum is disabled, please visit https://forum.opencv.org. During erosion, additional pixels are removed from the image boundaries. anchor: Anchor position inside the structuring element. Closing is reverse of Opening, Dilation followed by Erosion. Example #1 The result will look like the outline of the object. It is useful in closing small holes inside the foreground objects, or small black points on the object. opencv. We use the function: cv.erode (src, dst, kernel, anchor = new cv.Point(-1, -1), iterations = 1, borderType = cv.BORDER_CONSTANT, borderValue = cv.morphologyDefaultBorderValue()). morphologyEx (src, dst, op, kernel, anchor, iterations, borderType, borderValue). Step 2: Read the image. . border value in case of a constant border. Opening is just another name of erosion followed by dilation. OpenCV provides the following shapes: . Morphological operations are the set of operations that process images according to the given shapes. Opening is just another name of erosion followed by dilation. It is free for both commercial and non-commercial use. But in some cases, you may need elliptical/circular shaped kernels. Here are the examples of the csharp api class OpenCvSharp.Cv2.MorphologyEx(OpenCvSharp.InputArray, OpenCvSharp.OutputArray, OpenCvSharp.MorphTypes, OpenCvSharp.InputArray, System.Nullable, int, OpenCvSharp.BorderTypes, System.Nullable) taken from open source projects. It is usually used for removing internal noise present inside an image. In case of multi-channel images, each channel is processed independently. Right: final combined kernel. So what happends is that, all the pixels near boundary will be discarded depending upon the size of kernel. Here we use the function, cv.morphologyEx () opening = cv.morphologyEx (img, cv.MORPH_OPEN, kernel) Result: image. . OpenCV.js Tutorials Image Processing Morphological Transformations Goal We will learn different morphological operations like Erosion, Dilation, Opening, Closing etc. (c++ opencv)- - (zhihu.com) OpenCVC++,OpenCVC++ . . Then its variant forms like Opening, Closing, Gradient etc also comes into play. In other cases the anchor just regulates how much the result of the morphological operation is shifted. Because, erosion removes white noises, but it also shrinks our object. I have some captcha images and I want to do the same operation on them and get the same final result. Step 1: Import the libraries and read the image. Opening operation is similar to erosion in the sense that it also removes foreground pixels from the edges of the image. The closing operation is given by the expression: Below is the program demonstrating the Closing Morphological Operator: C++ Programming Foundation- Self Paced Course, Data Structures & Algorithms- Self Paced Course, Gradient | Morphological Transformations in OpenCV in C++, Opening | Morphological Transformations in OpenCV in C++, Erosion and Dilation | Morphological Transformations in OpenCV in C++, Python | Morphological Operations in Image Processing (Closing) | Set-2, Python | Morphological Operations in Image Processing (Opening) | Set-1, Python | Morphological Operations in Image Processing (Gradient) | Set-3, Image segmentation using Morphological operations in Python, OpenCV C++ Program to create a single colored blank image. Now, let's discuss how to implement this using OpenCV-Python. This means that we will apply dilation first, which is then followed by an erosion. The expression represents the fact that A is a sub-image of. acknowledge that you have read and understood our, Data Structure & Algorithm Classes (Live), Full Stack Development with React & Node JS (Live), Fundamentals of Java Collection Framework, Full Stack Development with React & Node JS(Live), GATE CS Original Papers and Official Keys, ISRO CS Original Papers and Official Keys, ISRO CS Syllabus for Scientist/Engineer Exam, Linear Regression (Python Implementation), Best Python libraries for Machine Learning, ML | Label Encoding of datasets in Python, Python | Decision Tree Regression using sklearn, Basic Concept of Classification (Data Mining), Program to draw circles using mouse moves in OpenGL. InputArraysrcMatCV_8U, CV_16U,CV_16S, CV_32F CV_64F. To know more about these and other basic morphological operations refer to previous tutorials (Eroding and Dilating) and (More Morphology Transformations). OpenCV . It is used in morphological operations such as erosion, dilation, opening, closing, gradient, black-hat/top-hat transform. This transform is also the basis of more advanced morphological operations such as thinning or pruning. input image; the number of channels can be arbitrary, but the depth should be one of cv.CV_8U, cv.CV_16U, cv.CV_16S, cv.CV_32F or cv.CV_64F. views 3. answers 1. vote 2015-10-05 14:14:25 -0500 sturkmen. The code is straightforward:-. We use the function: cv.getStructuringElement (shape, ksize, anchor = new cv.Point(-1, -1)). No wonder '32' appears much darker than '200'. 1. It is the difference between input image and Opening of the image. We use the function: cv.dilate (src, dst, kernel, anchor = new cv.Point(-1, -1), iterations = 1, borderType = cv.BORDER_CONSTANT, borderValue = cv.morphologyDefaultBorderValue()). morphologyEx dilate and erode isn't working properly.. c++. The two basic morphological operations are the erosion and the dilation. Erosion and dilation are the two basic morphological operations. It is useful in removing noise. 3Mat labels . Middle: kernel to 'miss'. 2. Left: kernel to 'hit'. Let's see an example: In this case, we are looking for a pattern in which the central pixel belongs to the background while the north, south, east, and west pixels belong to the foreground. We and our partners use cookies to Store and/or access information on a device.We and our partners use data for Personalised ads and content, ad and content measurement, audience insights and product development.An example of data being processed may be a unique identifier stored in a cookie. Python OpenCV Morphological operations are one of the Image processing techniques that processes image based on shape. We will see them one-by-one with help of following image: The basic idea of erosion is just like soil erosion only, it erodes away the boundaries of foreground object (Always try to keep foreground in white). If you want to understand it, please see this animation explaining the operation of Erosion. By voting up you can indicate which examples are most useful and appropriate.var cid='7301898925';var pid='ca-pub-6032030337406808';var slotId='div-gpt-ad-csharpcodi_com-medrectangle-3-0';var ffid=2;var alS=2021%1000;var container=document.getElementById(slotId);container.style.width='100%';var ins=document.createElement('ins');ins.id=slotId+'-asloaded';ins.className='adsbygoogle ezasloaded';ins.dataset.adClient=pid;ins.dataset.adChannel=cid;if(ffid==2){ins.dataset.fullWidthResponsive='true';} BlackHat transform is used to enhance dark objects of interest in a bright background. acknowledge that you have read and understood our, Data Structure & Algorithm Classes (Live), Full Stack Development with React & Node JS (Live), Fundamentals of Java Collection Framework, Full Stack Development with React & Node JS(Live), GATE CS Original Papers and Official Keys, ISRO CS Original Papers and Official Keys, ISRO CS Syllabus for Scientist/Engineer Exam, Linear Regression (Python Implementation), Best Python libraries for Machine Learning, ML | Label Encoding of datasets in Python, Python | Decision Tree Regression using sklearn, Basic Concept of Classification (Data Mining), Amplitude Modulation based on Depth of Modulation(Modulation Factor) using GNU Octave. We will learn different morphological operations like Erosion, Dilation, Opening, Closing etc. It is rectangular shape. It is the difference between dilation and erosion of an image. = - = - cv2.morphologyEx 12 cv2.MORPH_TOPHAT 3 img = cv2.imread (r"C:\Users\admin\Desktop\hb.jpg") kernel = np.ones ( (3, 3), np.uint8) tophat = cv2.morphologyEx (img, cv2.MORPH_TOPHAT . To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV The PR is proposed to the proper branch There is a reference to the original bug report and related work There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to . anchor position with the kernel. cvMorphologyEx (src1,dest1,NULL,NULL,CV_MOP_OPEN); It compiles fine but while running it gives me this error OpenCV Error: Bad flag (parameter or structure field) (Unrecognized or unsupport ed array type) in unknown function, file .\ocv\opencv\src\cxcore\cxarr ay.cpp, line 2476 OpenCV Morphological Operations Morphological operations are simple transformations applied to binary or grayscale images. Closing is reverse of Opening, Dilation followed by Erosion. It needs two inputs, one is our original image, second one is called structuring element or kernel which decides the nature of operation. The combination of these two operations generate advanced morphological transformations such as opening, closing, or top-hat transform. Erode the complement of image \(A\) ( \(A^c\)) with structuring element \(B_2\). Since noise is gone, they won't come back, but our object area increases. To view the purposes they believe they have legitimate interest for, or to object to this data processing use the vendor list link below. The number of channels can be arbitrary. We will use the OpenCV function morphologyEx () . The main issue is the (3,11) argument passed to cv2.morphologyEx. In this article, a Morphological operation called Opening is discussed. For that, we have used cv::Canny () edge detection algorithm. A-143, 9th Floor, Sovereign Corporate Tower, We use cookies to ensure you have the best browsing experience on our website. This function can be used for several operations, so we will need to add a parameter to specify which one we want to use. . import numpy import cypes libmatmult = ctypes.CDLL ("./cpp_function.so") def opencv_mat (a,b): # inits for cpp multiplications ND_POINTER_1 = numpy.ctypeslib . cv ::Mat element = cv ::getStructuringElement( cv ::MORPH_CROSS, cv ::Size(3, 3)); And now the core of the algorithm, the main loop. I am having a problem regarding the kernel size for morphologyEx. 1. The default value has a special meaning. anchor: Anchor position inside the structuring element.The default value is [-1, -1} signifying position as the center of the structuring element. Normally, in cases like noise removal, erosion is followed by dilation. cv2.morphologyEx | LearnOpenCV Invisibility Cloak using simple CV techniques in OpenCV Kaustubh Sadekar February 11, 2019 1 Comment Application Image Segmentation OpenCV OpenCV Beginners OpenCV Tutorials If you are a Harry Potter fan like me, you would know what an Invisibility Cloak is. Morphological opening of image (Binary image processing) [Note: We assume you have already installed OpenCV 3.4.3 or above along with opencv_contrib for your platform. The two basic morphological operations are the erosion and the dilation. It means that the output image will be of the same size as the input image. OpenCV provides the cv2.getStructuringElement() function to obtain the kernel. opencv-python1.myutils.py2.rmb.py . You may also want to check out all available functions/classes of the module cv2 , or try the search function . . 4. openCV ColorBlobDetector . It is useful for removing small white noises (as we have seen in colorspace chapter), detach two connected objects etc. morphologyex. So the thickness or size of the foreground object decreases or simply white region decreases in the image. Now, let's discuss thinning using hit-or-miss transform. We will learn different functions like : cv.erode (), cv.dilate (), cv.morphologyEx () etc. Passing (3,11) is probably like passing np.array ( [1, 1]) (or just undefined behavior). The depth should be one of cv.CV_8U, cv.CV_16U, cv.CV_16S, cv.CV_32F or cv.CV_64F. In this article, a Morphological Operator called Gradient is discussed. Use the OpenCV function cv::morphologyEx to apply Morphological Transformation such as: Opening Closing Morphological Gradient Top Hat Black Hat Theory Note The explanation below belongs to the book Learning OpenCV by Bradski and Kaehler. Morphological operators process images based on their shape. Theory Morphological transformations are some simple operations based on the image shape. It also helps in smoothening the contours and fusion of narrow breaks and long thin gulfs. 11k. It is normally performed on binary images. Here is a simple program demonstrating how to erode an image with a 3 x 3 kernel with OpenCV. In this article, a Morphological Operation called Closing is discussed. The code corresponding to the previous example is shown below. Therefore, the hit-or-miss operation comprises three steps: The structuring elements \(B_1\) and \(B_2\) can be combined into a single element \(B\). Gap Filling Contours / Lines. This processing strategy is usually performed on binary images. So what it does? The kernel slides through the image (as in 2D convolution). Mathematically, the operation applied to an image \(A\) can be expressed as follows: \[ A\circledast B = (A\ominus B_1) \cap (A^c\ominus B_2) \]. It is used for image segmentation and edge detection. output image of the same size and type as src. Just like the Opening operator it also uses a structuring element but it is used for removing small holes instead of pertusions. The operations of Morphological Operators are very simple, the main principle is the application of an element (in our case we have a block element of 33) into the pixels of the image. THRESH_OTSU) [1] cv_show ('thresh', thresh) img_save ('10.png', thresh) # thresh = cv2. By using our site, you 1 2 These operators apply one or more structuring elements to an input image to obtain the output image. Here, a pixel element is '1' if at least one pixel under the kernel is '1'. So it increases the white region in the image or size of foreground object increases. Closing. . We have to declare the structuring element we will use for our morphological operations, here we use a 3x3 cross-shaped structure element ( i.e. We can give different weights to different images, which can make the image transparent or translucent according to the weight added. System.loadLibrary(Core.NATIVE_LIBRARY_NAME); Kernel and output result for finding top-right corners, Kernel and output result for finding left end points, Extract horizontal and vertical lines by using morphological operations. https://anishdubey.com/install-opencv-dlib-ubuntu-18 Get full C++ and Python code It helps us to draw conclusions based on how it misses or fit in the image. morphologyEx (src, dst, op, kernel, anchor, iterations, borderType, borderValue) Parameters: src: It is the input image. How to use morphologyEx method in org.opencv.imgproc.Imgproc Best Java code snippets using org.opencv.imgproc. void morphologyEx( InputArray src, OutputArray dst, int op, InputArray kernel, Point anchor = Point(-1,-1), int iterations = 1, int borderType = BORDER_CONSTANT, const Scalar& borderValue = morphologyDefaultBorderValue() ) . In case of morphological operations, it is the minimum or maximum values, and so on. Step 3: Extracting Morphological gradient of an image Step 4: Displaying the output Step 1: Import the libraries and read the image. Opencv : How to correctly apply morphologyEx operation ? 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