Opencv python convolution kernel. Canny (). By default it is 3. Dec 1, 2019 · In image processing; kernel, convolution matrix, or mask is a small matrix used for blurring, sharpening, embossing, edge detection, and more. In a convolution operation (for example, stride = 2), a downsampled (smaller) output of the larger input is produced. Before, I use filter2d, like: filter2D(source, dest, img. Jul 20, 2015 · 2. We can use the filter2D () function of OpenCV to find the convolution of two matrices or an image with a kernel. def image_convolution(matrix, kernel): # kernel can be asymmetric but still needs to be odd k_height, k_width = kernel. zeros((nr, nc), dtype=np. py --image images/bricks. We shall implement high pass filter, low pass filter and a custom filter by changing kernel values. The filter2D () function finds the correlation between two matrices, but we can also use it to find the convolution. Second and third arguments are our minVal and maxVal respectively. Sep 12, 2016 · 10. Maybe, you need to use split () to process each channel independently. filter2D () which can be used to apply a convolution to an image. In this tutorial, we shall learn how to filter an image using 2D Convolution with cv2. png') result = cv2. Jan 2, 2021 · In my previous article I discussed the edge detection kernel, but I realized that I only stuck to greyscale images. Feb 26, 2022 · The filtering function actually calculates correlation. Apr 16, 2021 · First I use a square "open" kernel about the size of the small white spots to remove them. convolve(sig1, sig2, mode='valid') conv /= len(sig2) # Normalize. OpenCV blurs an image by applying what's called a Kernel. Flip the kernel both horizontally and vertically. The larger sigma, the more blure image. It simply takes the average of all the pixels under the kernel area and replaces the central element. Apr 14, 2023 · Dilated Convolution: It is a technique that expands the kernel (input) by inserting holes between its consecutive elements. Put the first element of the kernel at every pixel of the image (element of the image matrix). – If you want to do 4D convolution, you'll either have to use cv2. jpg', 0) # Define the Edge Detection Kernel. filter2D(), to convolve a kernel with an image Sep 25, 2016 · In your kernel you have "4" in the middle and "-8" as the sum of the other elements (weights) of the kernel. Note: if you are using Python you can alternatively use the function ndimage. Make it work as you expected May 19, 2019 · Then apply the convolution using the horizontal mask. So what happends is that, all the pixels near boundary will be discarded depending upon the size of kernel. If you need a real convolution, flip the kernel using flip() and set the new anchor to (kernel. The padded image has a width of iH + 2*pad, so this is running from pad pixels from the beginning to pad pixels from the end of an image column, such that one can index up to pad pixels in both directions without exiting the padded image. Let’s learn how to apply Sobel and Scharr kernels with OpenCV. plot(conv) Taking convolution using NumPy. In filter2D, we pass the kernel as a numpy array. This function computes convolution of an image with a kernel and outputs. # Inputs: # gray = a gray scale image. This is a problem with overflow/underflow of integer values, and/or a problem with image display. OpenCV only supports convolving an image where the output returned is the same size as the input image. Line 7: Using OpenCV’s filter2D () function we convolved the input image with the kernel. 6. Second input. shape[1] We can then apply the size formula for each output dimension: Jun 17, 2020 · 1. OpenCV puts all the above in single function, cv. It is the size of Sobel kernel used for find image gradients. Let's have a look. Below is a snippet that I use to smooth an image histogram. It is a matrix that represents the image in pixel intensity values. np. plt. Steps. The result of the convolution with your kernel has values outside of the [0,255] range, you need to figure out how you want to store those correctly and how to display them meaningfully. You just pass the shape and size of the kernel, you get the desired kernel. 0 - 1) + 0. Check the docs for more details about the kernel. The output consists only of those elements that do not rely on the zero-padding. Since OpenCV uses Numpy to display images, you can simply create a convolution kernel using Numpy. -1 -1 -1 -1 -1. filter2D(image, -1, convolution_kernel) For more information about kernel construction, look at this . The kernel is applied to every pixel in the image one-by-one to produce the final image (this operation known as a convolution). Feb 26, 2019 · @ShivamThakur: Yes, it would. Image Thresholding Application with Python and Aug 31, 2021 · For example, let's say we have the following kernel, where 2 represent such indicator values. This operation is the sister of dilation. A Kernel tells you how to change the value of any given pixel by combining it with different amounts of the neighboring pixels. Oct 20, 2019 · I am trying to find convolution in OpenCV using filter2D method but the result is not correct import cv2 as cv import scipy. Erosion. JPG image using OpenCV in Python. Feb 28, 2024 · The function cv2. 2. The fundamental and the most basic operation in image processing is convolution. Sigma determines width of filter (say size of filter). First argument is our input image. In Python, one popular library for image processing and computer vision is OpenCV. Sobel operators is a joint Gaussian smoothing plus differentiation operation, so it is more resistant to noise. Here we use the function, cv. # Outputs: Jul 27, 2021 · We can do kernel convolution in OpenCV using the filter2D method provided. Kernels are usually combinations of 1,0,-1 depending on the objective of kernel. Sep 3, 2018 · def conv_nested(image, kernel): """A naive implementation of convolution filter. . depth(), kernel, anchor, 0, borderMode); However, filter2D is a little bit slow when dealing 4 days ago · Place the kernel anchor on top of a determined pixel, with the rest of the kernel overlaying the corresponding local pixels in the image. // Initialize arguments for the filter. Dilation of the image is done by convolution of the image with a kernel of specified shape. Besides, why do you need to do convolution in frequency domain ? May 16, 2012 · I would suggest an original 2-step procedure (there may exist more efficient approaches), that uses opencv built-in functions : Step 1 : morphological dilation with a square kernel (corresponding to your neighborhood). Specifically, say your original curve has N points that are uniformly spaced along the x-axis (where N will generally be somewhere between 50 and 10,000 or so). py --image jemma. Aug 17, 2023 · The most common approach to image sharpening is to apply a sharpening filter or kernel to the image using convolution. signal. Python3. Apr 12, 2021 · gauss_filter = [np. Multiply the kernel coefficients by the corresponding image pixel values and sum the result. The erosion operation is: dst(x, y) =min(x. cols - anchor. A single-channel filter has just one kernel. Numpy has an FFT package to do this. Should have the same number of dimensions as in1. A LPF helps in removing noise, or blurring the image. convole I get meaningful results, for example, for this simple input image img 0 255 0 0 255 0 0 255 0 the convolution Stack Overflow Apr 12, 2017 · If your kernel is not symmetric (adjusted from the other answers):. 1. Here’s an example: import cv2. Sobel and Scharr Derivatives. For example, if we have two three-by-three Jan 18, 2024 · We’ll use Python with libraries such as OpenCV and NumPy to demonstrate this. png May 30, 2016 · If I apply a Sobel filter to an image in Python using scipy. In this article, we are going to see about the filter2d () function from OpenCV. Very many of these functions require convolving an image with a kernel, so this is the function I wrote to do that: def convolve (img, kernel): # img should have zero padding kx, ky = kernel. Convolve two N-dimensional arrays. # @ image : 2D image, as numpy array of size mxn. return np. morphologyEx () opening = cv. I created a function that takes an 'image' and a 'kernel' as parameters, and returns the grayscale version of the image. grad = signal. On the left, we have our original image. Multiply the two. 2-D Convolution. Let us see the two methods below: First load the original image. Also, the second derivative for an image is very sensitive to noise so a Gaussian blur can be applied first in which case the resulting filter can be thought of as an LoG (Laplacian of Gaussian). the result that has the same shape as the input image. Oct 16, 2021 · To install the following libraries, run the following commands in the command prompt: pip install opencv-python. filter2D looping over 2D submatrices of your 4D kernel, write it yourself manually, or use something else that supports it, like a deep learning package, or SciPy. Sep 27, 2022 · kernel − Convolution kernel. For details, see the function borderInterpolate() and discussion of the borderType parameter in the section and various functions below. array( [ [0, 1, 0], 4. This is a naive implementation of convolution using 4 nested for-loops. Jun 18, 2020 · xKernShape = kernel. The output of the NumPy implementation is identical to the Python-only implementation, which can be used to verify our implementation as well. filter2D(image, cv2. I would recommend using scipy to load in your image with imread from the ndimage package, convolve the image with your kernel, then convert to a PIL image when you're done. First input. If it is different than 1, the output is magnified by the value you put in kernel. "Open" removes white regions (or fills black gaps) and close removes black regions (or fills white gaps) Input: import cv2. Compute the FFT of both. Jan 3, 2023 · Python OpenCV – Filter2D () Function. For each placement, add all pixels under the kernel, take the average of pixels under the kernel and replace the central pixel with the average value. filter2D () function. Averaging. Convolve in1 and in2, with the output size determined by the mode argument. Convolution is the process of adding each element of the image to its local neighbors, weighted by the kernel. png' image = plt. Mar 14, 2023 · In the context of image processing and computer vision, convolutions are used to extract features from images. We will see how to use it. Aug 23, 2021 · And that's because the anchor of a (2, 2) kernel cannot be in the center of the kernel---in this case we see that with a centered pixel, the neighbors that dilate are only to the bottom-right, since it has to choose a direction because it can only expand the single pixel to fill up a (2, 2) square. ndimage. OpenCV has the function cv2. To do this, you need to create a Gaussian that's discretized at the same spatial scale as your curve, then just convolve. As our selected kernel is symmetric, the flipped kernel is equal to the original. ksize − The kernel size. It computes a local minimum over the area of given kernel. png. Here’s a general overview of how image sharpening works: 1. This step gives you another image, after replacing each pixel value by the maximum value inside the kernel. These three add up to one flowing by bias and activation. Oct 10, 2023 · Use the filter2D () Function of OpenCV to Find Convolution of Matrices or Images in Python. You will need more 2's to detect lines of the width you are looking for. y - 1). You can always view a 1D vector as a 2D mat, and thus simply calling the opencv build-it functions resolves the problem. shape[0] yKernShape = kernel. Jan 26, 2016 · Now, you can do your convolution using this kernel. This can be achieved by using Kernels. The last parameter is the kernel provided by the user. Pad them with zeros to make their sizes match. If it is all 0, the output will be 0. finally, this is one Sep 1, 2020 · I am implementing my convolution logic for image filtering in Python, but it is only rendering a black image every time for different input images and kernels. It is useful in removing noise, as we explained above. [(7, 7), (100, 100)] then it might be as simple as getting the appropriate image patch (say the same size as your provided kernel), convolve the image patch and kernel, and insert back into the original image. If only one have the value 255' then 255 is added to result also. If it is greater than size of input This video provides you with a complete tutorial on the code walkthrough of OpenCV convolution kernel. Figure 8. Here, the filter2D function does the convolving task by taking in the img and the kernel as a parameter. python image_blur. It is 1, to keep the pixel value as is, and ALL 1 because that is what erosion filter does. Inside of the function I split the image into 3 individual channels: redChannel, greenChannel, and blueChannel. This is done by the function cv. image_blurred = cv2. signal as sig import numpy as np b=np. One thing I forgot to say here: Convolutions through the FFT are only efficient for larger kernels. x - 1, kernel. To act as a helpful guide, I shall discuss how we can go about applying these kernels onto colored images while still retaining the core image. You can execute the code by using the following command. I think there is some built in function that does it but I don't really understand it from the places I have seen it, and it seems that there are more than one possible ways to do it in opencv. array(gauss_filter) And 2d convolution function which performs a 2D convolution between image and filt, image being a 2D image. For a small kernel such as the 3x3 kernel here or a Sobel kernel, you are better off not using the FFT at all. So what does it do? The kernel slides through the image (as in 2D convolution). Closing. Jun 12, 2017 · We manually created a structuring elements in the previous examples with help of Numpy. In all the following Python examples, the required Python library In Convolution Neural Network, Convolution operation is implemented as follows, (NOTE: COnvolution in blur / filter operation is separate) For RGB-like inputs, the filter is actually 223, each filter corresponse to one color channel, resulting three filter response. Feb 16, 2016 · If you read a bit further down in the description in the OpenCV documentation: The function does actually compute correlation, not the convolution: That is, the kernel is not mirrored around the anchor point. def myconv2(image, filt): # INPUTS. Convolution slides a kernel matrix across the image matrix horizontally and vertically. anchor = Point ( -1, -1 ); delta = 0; ddepth = -1; Loop. However, the results between this 'manual' convolution and cv2::filter2D are quite different as can be seen in the attached picture. This tutorial is meant to help you learn how to code a 5 days ago · Canny Edge Detection in OpenCV. Apr 26, 2016 · All I want to do is apply a custom convolution matrix (kernel) to an image (mat or any other format is fine) in opencv. The function uses the DFT-based algorithm in case of sufficiently large kernels (~11 x 11 or larger) and the direct algorithm for small kernels. It performs convolution of the original image by a kernel of a square matrix of size 3X3 or 5X5 etc. Example of applying a blur filter with the convolution process using the code in Listing 1. Apr 21, 2015 · I don't know of any function that does exactly what you're asking. The weights in a filter/kernel are initialized to small random values and are learned by the network during training. The kernel has an anchor point which is by default positioned at the center of the kernel. Be sure to access the “Downloads” section of this tutorial to retrieve the source code and example images. Assuming that your image kernel is odd, you can simply divide each of Mar 19, 2014 · The most similar kernel for Laplacian to yours would be [ [0,1,0], [1,-4,1], [0,1,0]] for a 2D image. Its first argument is the input image, which is grayscale. Original image (left), image after convolution with kernel blur_3x3 (centre) and image after That is, the kernel is not mirrored around the anchor point. filter2D(src, ddepth, kernel) src: The source image on which to apply the fitler. Jun 10, 2014 · 1 Answer. Let's analyze that more in detail: First we define the kernel our filter is going to use. Fourth argument is aperture_size. May 2, 2022 · Answer. If you have a symmetrical convolution kernel, the mathematical expressions for correlation and convolution are the same. If the kernel is not symmetric, you must flip the kernel and set the anchor point to (kernel. Aug 1, 2022 · import numpy as np. arange(pad, iH + pad) runs over iH pixels, which is the width of the original input image. Place the result to the location of the anchor in the input image. shape # kernel is square so kx == ky start, end = floor (kx / 2), ceil (kx 2D Convolution ( Image Filtering )¶ As for one-dimensional signals, images also can be filtered with various low-pass filters (LPF), high-pass filters (HPF), etc. -1/2 0 1/2. Sorted by: 2. 2 2 2 2 2. pip install numpy. In gaussian filter, we have to determine sigma or standarad deviation of filter. imread(img_path) plt. Then each element of the kernel will stand on top of an element of the image matrix. rows - anchor. Below is the code def 4 days ago · First we will see how to find Fourier Transform using Numpy. The code will consist of loading an image, defining a kernel, and then applying the convolution operation. You can specify the direction of derivatives to be taken, vertical or May 7, 2014 · Well, as far as I know, OpenCV image filtering can not use more than one channel filter kernel. With the help of that, by performing convolution, it generates the output. OpenCV by default uses the following: sigma = 0. It is a method of adding pixels to the boundaries of objects in an image. Aug 24, 2021 · np. Here are some common kernels and the result after convolving. So for this purpose, OpenCV has a function, cv2. See OpenCV documentation for filter2D. If your kernel is complex, then your data may be stored as a 2-channel vector/matrix. # smoothing_nbins = int, the width of 1D filter. 2- Apply some kind of padding to image, meaning that enlarge your image in a specific way temporarily so that you can apply apply convolution kernel to values at the edge. Then run filter2D (convolution function for images) in opencv. You multiply kernel values by pixel values. If both pixels are 0 then 0 added to result. The first parameter is the input image, the second parameter ddepth=-1 indicates that the depth of the output image will be same as the input image. Convolution uses a 2input matrix: that is, image matrix and kernel. If you need a real convolution, flip the kernel using flip and set the new anchor to (kernel. (y,x) of input Image (I) is anchor point of kernel, to assign new value to I(y,x) you need to multiply every k coefficient by corresponding point of I - your code doesn't do it. The averaging part is handled by dividing the kernel values by 9 (since it is a 3x3 matrix). imread('1. Treat your matrix as an image and use opencv. imshow(image) Nov 15, 2021 · I am writing a python script that would use a 3x3 kernel to convert an image from color to grayscale. kernel = np. As you change the kernel, you can also notice the change in the output. Jan 8, 2013 · Initialize the arguments. import cv2 from matplotlib import pyplot as plt import numpy as np img_path = 'Lena. To run our script (and visualize the output of various convolution operations), just issue the following command: $ python convolutions. 3. Repeat the process for all pixels by scanning scipy. conv = np. With second way, size of window can be determined . Args: Mar 5, 2012 · We can obtain the same result by using a convolution kernel where the coefficients are written in the place of the corresponding neighbor pixel: -1/2 0 1/2. fft2 () provides us the frequency transform which will be a complex array. However, the only difference is that the filter kernel (your second kernel) needs to be flipped. We will see each one of them. Aug 17, 2019 · 1 Answer. asarray([[1,2,0,1,2], 3 days ago · OpenCV provides four main types of blurring techniques. exp((-x**2) / (2*sigma**2)) for x in rng] # The formula used above has been given in the instruction. pad(matrix, (int(k_size/2), int(k_size/2))) if k_size > 1: if k_height == 1: padded = padded[1:-1,:] elif k_width == 1: padded Dec 25, 2015 · I would like to implement a convolution between an image and a kernel, somewhat like MATLAB conv2(img, kernel,'same'), which indicates that the result image is the same size as the original image. rows - anchor Mar 17, 2017 · To answer your specifiy questions: Is the cv2. import numpy as np. May 12, 2021 · Sobel and Scharr kernel results. The matrix operation being performed—convolution—is not traditional matrix multiplication, despite being similarly denoted by *. Compute the complex conjugate of the FFT of the watermark image (this corresponds to flipping the image vertically and horizontally in the spatial domain). Syntax: filter2D (src, dst, ddepth, kernel) Jun 7, 2023 · Figure 3. Nov 1, 2021 · You have mixed the Opencv's inbuilt method of Gaussian blurring and custom kernel filtering method. You can specify the direction of derivatives to be taken, vertical or Dilation in OpenCV. The output is the full discrete linear convolution of the inputs. convolution_kernel = np. For a 3-pixel width horizontal line, you will need the following kernel. The output is the same size as in1, centered with respect to the ‘full May 4, 2020 · cv2. If instead of providing a mask of points to be convolved you provided a list of points ex. import cv2 image = cv2. Then I use a horizontal rectangle "close" kernel about the size of the black gap to fill it. Nov 9, 2019 · 1- Ignore values of the edges, eg. For thicker lines, you need a larger kernel in the conventions of your link. We will simply take a transpose of the mask and flip it along horizontal axis. MORPH_OPEN, kernel) Result: image. blur() or cv. Change the shape of your array to be [height, width, num_channels]. Load the image: Read the image using OpenCV’s imread function and store it in a Sep 9, 2021 · I took on a challenge to implement a few OpenCV functions on my own in Python. py --blur median_blur. 4. But in some cases, you may need elliptical/circular shaped kernels. Perform an infinite loop updating the kernel size and applying our linear filter to the input image. There are two way to specify width of filter, one is window size and second is sigma. In Python, OpenCV provides functions to perform convolution and apply filters. – Cris Luengo. Reference 4 days ago · Opening is just another name of erosion followed by dilation. This is done by convolving an image with a normalized box filter. On line 2, we are applying the median blurring to the image with a kernel size of 5. pip install matplotlib. Convolution in NumPy. Let’s get started! As always let us begin by importing the required Python Libraries. In a nutshell, with this function, we can convolve an image with the kernel (typically a 2d matrix) to apply a filter on the images. if your kernel is 3x3, ignore elements at the edges, if your kernel is 5x5, ignore last 2 elements at the edges and so on. Oct 29, 2018 · Make sure the two images (distance transform and edges of watermark) are the same size. As such, you can still use OpenCV's filter functions, but simply ignore those pixels along the edges where the kernel didn't fully encapsulate itself inside the image. Import the required library. convolve2d(gray, gaussian_kernel, boundary=’symm’, mode=’same’) Object Detection with Python using Jan 8, 2013 · Perform a convolution with the same kernel shown above (multiplied by 4) to approximate the values of the "missing pixels" These two procedures (downsampling and upsampling as explained above) are implemented by the OpenCV functions pyrUp() and pyrDown() , as we will see in an example with the code below: Nov 23, 2019 · I am trying to perform edge detection for my images of soil grains using holistically nested edge detection method HED as shown however when using combined fine and coarse soil grains , the region of fine particles is not clear so I suggest making image convolution by cutting the image into smaller rectangular areas in both directions and make Each channel in a filter is referred to as a kernel so that you can think of a filter as a container for kernels. float32) #fill The output is the full discrete linear convolution of the inputs. 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). Jan 8, 2013 · OpenCV provides four main types of blurring techniques. 8. 1 Answer. Therefore, in this case, the filter and the kernel are one and the same. For comparison I also created a simple convolution function that slides a kernel over every pixel in the image. From there, open a terminal window and execute the following command: $ python opencv_sobel_scharr. shape[1] xImgShape = image. filter2D () is utilized to apply a custom kernel to an image, with arguments specifying the depth of the output image. gaussian_filter1d(data, sigma=1, order=1, mode='wrap') from from scipy import ndimage. waitKey(0) If we give the command line blur type as median_blur, then the above code block will execute. Second argument is optional which decides the size of output array. boxFilter(). Nov 17, 2017 · In this video, we will learn the following concepts, Kernel ConvolutionPlease refer the following Wikipedia link for knowing more about kernels,https://en. Jan 8, 2013 · OpenCV provides three types of gradient filters or High-pass filters, Sobel, Scharr and Laplacian. image = cv2. A HPF filters helps in finding edges in an image. In boxFilter, we pass only the kernel size as a tuple. Here is the output: In order to combine both the vertical and horizontal edges (derivatives) we can use the following equation: G = √G2 x +G2 y G = G x 2 + G y 2. ones((3,3)) / 9. convolve #. First you need to create dst matrix with dimenstion as original image, and the same type of pixel. OpenCV provides a function, cv2. Python. (Default) valid. Syntax to define filter2D () function in python is as follows: resulting_image = cv2. To perform bilateral filter operation, you can follow the steps given below −. Then the point spacing along the x-axis will be Feb 5, 2020 · 1. filters. shape[0] yImgShape = image. CV_64F, kernel) # will apply the kernel for each channel. G_x = -2 0 2. In simpler terms, it is the same as convolution but it involves pixel skipping, so as to cover a larger area of the input. You’ll then see the results of applying the smallBlur kernel to the input image in Figure 4. If you don't want to deal with fractions, you multiply this by 2 and get the well-known Sobel 3x3 kernel. I am starting to learn this myself but here is a Jul 15, 2015 · OpenCV is a pain to configure even though it's quite powerful. Need help. Oct 12, 2020 · I am playing around with an edge detection algorithm on a . In ‘valid’ mode, either in1 or in2 must be at least as large as the other in every dimension. Closing is reverse of Opening, Dilation followed by Erosion. 3 * (kernel_size / 2. As the kernel B is scanned over the image, we compute the minimal pixel value overlapped by B and replace the image pixel under the anchor point with that minimal value. (Default) 5 days ago · OpenCV provides three types of gradient filters or High-pass filters, Sobel, Scharr and Laplacian. morphologyEx (img, cv. I am trying to perform a 2d convolution in python using numpy I have a 2d array as follows with kernel H_r for the rows and H_c for the columns data = np. So put 8 in the middle and also consider that you have set your canvas type to 8-bit unsigned int (integer values from 0 to 255). imread('example. Jul 6, 2021 · Fractionally-strided convolution, also known as transposed convolution, is the opposite of a convolution operation. shape m_height, m_width = matrix. filter2D () function able to convolve two kernels? Yes, but by default, it actually computes the correlation, not the convolution. The easiest solution I can suggest without you having to write one or hack at one yourself is to use SciPy's scipy Aug 8, 2021 · Convolution is nothing but a simple mathematical function, which is used for various image filtering techniques. This is related to a form of mathematical convolution. May 14, 2021 · Convolution Results. Whereas in a fractionally-strided operation, an upsampled (larger) output is obtained from a smaller input. Step 2 : test if Jan 8, 2013 · Opening is just another name of erosion followed by dilation. It is rectangular shape. shape k_size = max(k_height, k_width) padded = np. Dec 2, 2018 · Step2: 用剛剛求得的 3*3 gaussian_kernel對圖片做Convolution. Dilated convolution, also known as atrous convolution, is a type of convolution operation used in OpenCV enables you to specify the extrapolation method. # Read the image. Sep 25, 2021 · This method can enhance or remove certain features of an image to create a new image. fft. The convolution happens between source image and kernel. -1 0 1. If both pixels on image, which correspond to that elements in kernel have the value '255' then 255 is added to result of convolution, not 500. same. getStructuringElement(). pu ft la bw jp xw dh js zr ix