Sliding window technique in image processing matlab

sliding window technique in image processing matlab Mar 14, 2019 · Image processing. Edge density is evaluated on integral image calculated from the input image. JPG’); Now call imshow to display I Jan 01, 2017 · 2. We realized that using these techniques, we could build an intuitive, low-cost and tangible interface. Sliding window technique is often used with an image classifier in an object detection field to determine the content that is located in the window. In MATLAB Image Processing Toolbox has imrotate() function for rotating image. You, a free software hippie, are using Debian 7. Nov 12, 2021 · Image processing is a method to perform operations on an image to extract information from it or enhance it. pdf), Text File (. topic in the list. where the sigmoid function used with the maximum and minimum Dec 11, 2018 · Answers (1) There are many ways you can apply the sliding window. May 22, 2014 · The body force isthe link with image data and is defined from the proposed LSE. Greenberg et al. In computing this median, medfilt1 assumes zeros beyond the input points. Apr 23, 2014 · I am implementing HOG for people detecting, however, I have problem on sliding window technique to detect multiple people in images. At each window position the sampled values of signal or image are sorted, and the median The image in this tutorial depicts a scene that independently has a “right side up”. 6. Image Processing MATLAB Thesis for PhD Students offers you world class thesis for your projects in MATLAB, which will improve your academic performance. 1. Describes how to display images and explore images using the Image Tool. Sliding Window Machine Learning Approach In the sliding window approach, a window of suitable size, say m x n, is chosen to perform a search over the target image [8, 9]. geeksforgeeks. This partitioning will result in K = (Ns -N +1) (Mt -M +1) snapshot matrices being generated for processing. It can be divided into two types: analog image processing and digital image processing. Here we go… Following a code in MATLAB function that apply salt & pepper noise to an image. Sliding window recon for real-time data. can be represented by a regular 1D vector in Matlab). 1. Keywords: MATLAB, digital, image, processing, Fundamental 1. 3. Displaying and Exploring Images. Matlab program of subtraction radiograph was used to execute the subtraction between original image f(x,y) and background of original image h(x,y). The median filter replaces the center value in the window with the median value of all the points within the window . You can use spatial referencing objects, which encode the location of the image in a world coordinate system, the image resolution, and how the image extent relates to intrinsic and world coordinates. Aug 23, 2017 · Image filtering is the process of removing these errors. we actually convolve the image matrix with a. Digital Signal Processing Using MATLAB Cover Image: c Marilyn Volan/Shutterstock 7. Dec 29, 2011 · The radar transmits an Mt-pulse waveform in its coherent processing interval (CPI). Color image processing is the topic Dec 18, 2013 · Spread the loveBackground subtraction, also known as Foreground Detection, is a technique in the fields of image processing and computer vision wherein an image’s foreground is extracted for further processing (object recognition etc. Object counting, which is the estimation of the number of objects in a still image or video frame, is a tedious and time consuming task in image processing. Image sampling and quantization, color, point operations, segmentation, morphological image processing, linear image filtering and correlation, image transforms, eigenimages, multiresolution image processing, noise reduction and restoration Generally there are two types of • Image processing is a natural fit for data parallel processing - Pixels can be mapped directly to threads fast box filter • Allows box filter of any width with a constant cost - Rolling box filter • Uses a sliding window - Two adds and a multiply per output pixelThere are two types: 1. ) in its foreground. Hence, a lung cancer detection system using image processing is used to classify the present of lung cancer in an CT-images. indicating the presence of a pedestrian. There are two basic ways to create graphs in MATLAB. Listing 2 represents the corresponding MATLAB code but in a general form of the sliding window that will be used and discussed further. Perceptually, we infer 3D shape from images using shading. Image Row 0 must always be displayed at the top. There are several ways to define a world coordinate system. Next, each intermediate pixel is set to the value of the minimum/maximum grayscale value within the given radius and distance metric. Every process requires a different technique. For a given pixel, a 9-by-7 pixel window is considered around it. A standard median operation is implemented by sliding window of odd size (e. 3 Window Design Techniques 324 Edge detection is an image processing technique for finding the boundaries of objects within images. Otsu's method chooses a threshold that minimizes the intraclass variance of the thresholded black and white pixels. Convolving a noisy image with an appropriate kernel practically nullifies the noise. deviation and sliding neighborhood as stages during processing of fingerprint image. Image processing is the technique to convert an image into digital format and perform operations on it to get an enhanced image or extract some useful information from it. Analog image processing is to process analog images by using optical, photographic and electronic methods. Image Processing Toolbox apps let you automate common image processing workflows. red (R), green (G), and . Object Counting In Image Processing. 3x3 window) over an image. The convolution f g of f and g is de ned as: (f g)(i) = Xm j=1 g(j) f(i j + m=2) One way to think of this operation is that we’re sliding the kernel over the input image. Image Processing Using MATLAB - Free download as PDF File (. The diagnosing methodology uses Image processing methods and Support Vector Machine (SVM) algorithm. The post-processing methods use this output to compute the bounding boxes. In this paper a novel technique to implement Image Processing Toolbox mean sliding window variance. It works by detecting discontinuities in brightness. You can run MATLAB 6 with the old interface by starting the program withth e command matlab /nodesktop on a Windows system or matlab -nodesktop on a UNIX system. org/coursesThis video is contributed by Anant Patni. Convolution and correlation, predefined and custom filters, nonlinear Apr 26, 2018 · Figure 9. In the Help browser, expand the Image Processing . This is a common technique to use with geospatial data. Figure 13. function [output_image] = applyNoise(input_image) output_image=imnoise(input_image BIMI. Finally, using the location of the two detected lane lines and the assumption that the camera is located at the centre of the image, we then calculate the position of the car relative to the lane. PhD students are also heartily invited to join with this service at any time. For all the below filters, let the kernel size be K height *K width. In modern digital image processing data de-noising is a well- known problem and it is Sliding window algorithm is used to perform required operation on specific window size of given large buffer or array. Image enhancement is the process of adjusting images so that the results are more suitable for display or further image analysis. The first string Nk=sum(kernel(:)); calculates the A sliding window framework for classification of high resolution whole-slide images, often microscopy or histopathology images. 3 represents the Matlab based projects,Matlab Projects in Bangalore,IEEE matlab projects in bangalore,IEEE 2021 matlab projects bangalore,ieee projects on signal processing using matlab,Matlab Medical Image Processing,Matlab Projects Bangalore,Matlab Projects in Bangalore,IEEE Matlab Projects,IEEE 2021 Matlab Projects,matlab project centers in bangalore,simulink projects,matlab project ideas,matlab project The DSM was first normalized by subtracting from it the ground height, computed as the set of smaller local maxima in a sliding window analysis. % Zero-padding convolution will be used if no border handling is specified. Image Filtering. Edges are often associated with the boundaries of objects in a scene. Image processing operations implemented with filtering include Image Source: Jain, R. Apr 28, 2021 · Displacements may be derived from an image pair either with a single pass across the images or with multiple passes with gradually reducing window sizes (Thielicke and Stamhuis, 2014; Raffel et al. In an image, an edge is a curve that follows a path of rapid change in image intensity. By default, clicking and dragging the mouse in the slice displayed interactively changes their brightness and contrast, a technique called window/level. If the blocks overlap you can use nlfilter or colfilt, or even simpler since your operation is simply a sum conv2. hello, does anyone know how can we convert intensity image (grayscale image) to range image? I want to image proccessing the lidar image and I need range image . CSCT for the center pixel in that window is estimated by comparing the value of each pixel with its corresponding center-symmetric counterpart in the window. به دلیل وجود تعداد زیاد مقالات شبیه سازی شده در زمینه برق کنترل و سهولت دسترسی شما مخاطب عزیز, این شبیه سازی ها را در دو لینک جداگانه Sep 17, 2020 · In this article, we talk about digital image processing and the role of AI in it. The proposed LSM is then implemented using an NVIDIA graphics processing units to fully take advantage of the LBM local nature. By using this new dataset, another CNN is re-trained which can separate cells into T-cells and B-cells. Building GUIs with Modular Tools. % Convolution is done layer-by-layer. Toolbox بانک مقالات آماده برق کنترل - سفارش انجام پروژه های متلب. Describes how the toolbox handles various types of images and describes the toolbox arithmetic functions. Dec 23, 2014 · Your image is 364x350, and the window size is 32x32. Sliding window method plays a critical role to determine the location of palm tree in a Nov 29, 2013 · Image denoising (1) Image encryption (2) Image Fusion (4) Image Negatives (1) Image Processing Fundamentals (80) Image Processing Project (86) Image Processing Projects (66) Image restoration (2) Image segmentation (1) Image Thresholding (4) Information Security (43) MATLAB Basics (81) MATLAB code (75) MATLAB fundamentals (72) MATLAB GUI (88 In image processing whenever we are applying a transformation on. Like other image arithmetic operators, multiplication comes in two main forms. Jun 03, 1999 · The Image Processing Toolbox User’s Guide is available online in both HTML and PDF formats. 1 MATLAB® platform Since a fluence map of dose intensity matrix is processed in SWIMRT, and some simple im- age-processing routines are added to the program, a software platform that involves the manipulation of large arrays and matrixes should be used to develop SWIMRT. the picture matrix for blurring, sharpening, embossing, edgedetection, etc. Let's read in a JPEG image named image4. It appears in a wide range of domains: biology (cell counting in microscopic images), surveillance systems (crowd monitoring), biodiversity (animal Aug 13, 2013 · The objective is to achieve contrast enhancement is to improve the contrast of lesions for easy detection using a w*w sliding window with assumption that w is large enough to contain a statistically representative distribution of the local variation of lesions MATLAB: Sliding window in image. Fundamental processes underlying these techniques include sharpening, noise removal, deblurring, edge extraction, binarisation, contrast enhancement, and object segmentation and labeling. The user can either import a fluence map with a graphical file format created by an ext … Nov 12, 2015 · Answers (1) you can perform what you're doing a bit simpler. 6 for the segmentation methods which suffer from under segmentation due to street texture or sidewalk. In this Lecture-21:Transfer Function Response and Bode plot (Hindi/Urdu) Oct 21, 2020 · Welcome to the "Image Processing Made Easy" webinar. For example, you can filter an image to emphasize certain features or remove other features. The content of the window will pass through an image classifier before it proceeds to the next window. Image mirroring Mirroring technique is the rotating of reversed image on the horizontal axis. 7 for the sliding window and between 0. Edge detection is used for image segmentation and data extraction in areas such as image processing, computer vision, and machine vision. Background subtraction is a widely used approach […] this on the testing examples derives the classification guesses for the testing dataset face detection via sliding window, malaria parasite detection using image processing face recognition using image processing matlab pro matlab project with A flat structuring element is a binary valued neighborhood, either 2-D or multidimensional, in which the true pixels are included in the morphological computation, and the false pixels are not. Sep 28, 2021 · Commented: DGM on 29 Sep 2021 at 7:15. The received data can then be partitioned in both space and time, by using a sliding window, into an (N*M) space-time snapshot X'. S. Fig. The low-pass filters usually employ moving window operator which affects one pixel of the image at a time, changing its value by some function Basic operations with matlab image processing tool box Read and Display an Image: Clear the MATLAB workspace of any variables and close the open figure windows. thanks! The chapter relates to the Image Processing Toolbox in MATLAB. Filtering consists of neighborhood operations that can be used to sharpen details, blur edges, remove random noise, and is developed for the recognition of the loaded face image using svm and surf technique step 5 at last code is developed to analyze our result using, hog feature implementation with svm in matlab i extract hog features using matlab code in this page for the dalal triggs variant for example i have Jul 07, 2014 · Windows macOS Linux Categories Image Processing and Computer Vision > Computer Vision Toolbox > Recognition, Object Detection, and Semantic Segmentation > Object Detection Using Features > A MATLAB Answers thread below talks about the Sliding Window Technicque: Sliding Window Technique in MATLAB. If you are a Windows user, you Nov 26, 2018 · First create a folder for the project (my folder name is Number Plate Detection) to save and store the files. Mar 01, 2018 · Read part 1 Image processing covers a wide and diverse array of techniques and algorithms. Software will be written in Matlab or C/C++ to implement the image processing method. Different algorithms are suited for detecting edges of straight lines, round objects, or arbitrarily shaped regions. This tutorial does not contain all of the functions available in MATLAB. [4] proposed two methods for image enhancement. The objective is to find the minimum k numbers present in each window. image processing sliding window. A custom-made computer program, SWIMRT, to construct "multileaf collimator (MLC) machine" file for intensity-modulated radiotherapy (IMRT) fluence maps was developed using MATLAB and the sliding window algorithm. It includes high-level functions for two-dimensional and three-dimensional data visualization, image processing, animation, and presentation graphics. For contiguous, non-overlapping blocks you can use blockproc. The edge of the image is applied using the Canny gradient [3, 4, 29] shown in Figure 1(c). Convolution and correlation, predefined and custom filters, nonlinear filtering, edge-preserving filters. Winter 2019-20. II. The toolbox supports processing of 2D, 3D, and arbitrarily large images. stWindow = sum (tWindow); % then take the sum to count how many are over the threshold per column (you'll end up with a 1x3 matrix of how many are over the threshold. (2) where MATLAB Image Processing Assignment Help. First, the model computes the CSCT on each of the left and right images using a sliding window. Image transparency overlay with GNU Octave using YCbCr. Vehicle/Lane Position. Image Processing by using MATLAB Editor Window How to make GUI with MATLAB Guide Part 2 - MATLAB Tutorial (MAT & CAD Tips) This Video is the next part of the previous video. Sudhanshu Bhatt. Learn more about range image 3. Image rotate. The answer to problems involving a sliding window is very often to use the convolution operation, as here. Further preprocessing steps included compensation of the shaded area in the image and statistical analysis of the training samples. 6 and 0. EE368/CS232: Digital Image Processing. Sep 28, 2021 · how to create range image?. This greatly reduces the computational cost incurred when running filter is very widely used in digital signal and image/video processing applications. We also evaluate the average overlap between detection and ground truth rectangles. The global threshold T can be used with imbinarize to convert a grayscale image to a binary image. Common edge detection Description. After you click the mouse to capture a point, the recorded point will appear as a red dot in the capture window and the reference window will show the next point to captured. , Schunck, B. Everybody likes to play music, if not, to at least listen to music. Filtering is a technique for modifying or enhancing an image. , 2018). The envelope image was obtained from the absolute value of M-files, a series of MATLAB statements that implement specialized image processing algorithms You can view the MATLAB code for these functions using the statement type function_name You can extend the capabilities of the Image Processing Toolbox by writing your own M-files, or by using the toolbox in combination with other toolboxes, such as Image Processing Toolbox User's Guide. Image processing is a very popular field that we see a lot of our customers use extensively for designing vision-based systems across a variety of different application spaces like automated driving, robotics, machine vision, and medical imaging, just to name a few. Instead of classifying every region using a sliding window, the R-CNN detector only processes those regions that are likely to contain an object. Window starts from the 1st element and keeps shifting right by one element. In this article, we will be covering the top 6 […] 1. Morphological Operation: The term morphological image The window on the right is the capture window you click the mouse to capture the corresponding points. 13. To access the PDF help, click on Image Processing . This program uses the sliding window algorithm to compute a minimum or maximum filter on a color image. Generally an image’s regions of interest are objects (humans, cars, text etc. bothth e Windows and UNIX versions of MATLAB 6, it may also run more slowly than the MATLAB 5 Command Window interface, especially on older computers. For this reason, many of the techniques developed for monochrome images can be ex-tended to color images by processing the three component images individually. blue (B) primary (or . Jan 26, 2013 · I will explain how to read an image in C# and pass it to MATLAB for processing. We describe some AI-based image processing tools and techniques you may use for developing intelligent applications. NOISE REMOVAL TECHNIQUES Image de-noising is very important task in image processing for the analysis of images. The digital image processing class introduced us to techniques that could be used to quantify human gestures and movements. So, let's say someone sends you a Matlab file displaying interesting image regions using the AlphaData figure property. tstwindow = stWindow>windowL/2; % then you can threshold again to see which ones have a majority over the threshold. For example, you can remove noise, sharpen, or adjust the contrast of an image, making it easier to identify key features. How can i use a 32×32 sliding window on an image and extract glcm feaures from that? Best Answer. 2. 5 and 0. In this study, MATLAB have been used through every procedures made. The dermoscopy image of skin cancer is taken and it goes under various pre-processing technique for noise removal and image enhancement. ). To access the HTML help, select Help from the menu bar of the MATLAB desktop. A fivefold cross validation is used to assess the performance. Jul 10, 2021 · function ImOut = convImage ( Im, Ker, varargin) % ImOut = convImage (Im, Ker) % Filters an image using sliding-window kernel convolution. 5 Image Processing Toolbox Tutorial The purpose of this tutorial is to gain familiarity with MATLAB’s Image Processing Toolbox. This function needs three properties which are image matrix variable, rotating angle, and interpolation method (Figure 13). The function medfilt1 implements one-dimensional median filtering, a nonlinear technique that applies a sliding window to a sequence. After finishing this chapter, you can use MATLAB Image Processing Toolbox and write script for processing of images. Course Description. Here, we will show you both the methods to perform basic operations of image processing in MATLAB. Left image of breast cancer a class of abnormality MISC pre-processing a) input image R-CNN is an object detection framework, which uses a convolutional neural network (CNN) to classify image regions within an image [1]. In this project, we explore an image processing technique known as filtering to modify and enhance pictures. Oct 15, 2020 · You can perform image segmentation, image enhancement, noise reduction, geometric transformations, and image registration using deep learning and traditional image processing techniques. At each window position the sampled values ofsignal or image are sorted, and the median value of the samples replaces the sample inthe center of the window as shown in Figure 3. 2 Image Processing Image processing refers to the technique of performing a series of operations on an image to achieve some desired purposes [1–3]. Toolbox. -1. Jan 20, 2017 · The algorithm of Nakagami imaging was based on the sliding window processing, which was the same technique as that described in Fig. The results of the present research are shown in figures (1-6). Dragging the mouse horizontally from left to right changes the contrast. Digital image processing has a broad range of applications such as image restoration, medical imaging, remote sensing, image segmentation, etc. GRADING: Test #1 - 25%, Test #2 - 25%, Homework & Lab Exercises - 25%, Project - 25% . My name is Sandeep, and I'm into product marketing team here at MathWorks. This is given by the N-MODP that lies between 0. txt) or read online for free. Our courses : https://practice. However, if the shape of the object in the image is known, you could setup a shape template of the white glare (gaussian) and do a sliding window to find possible detection of glare (followed by color blending from adjacent area). process is applied to carry out by sliding a window over the image by removing the unwanted part from the original image. After that window size is increased and again condition is checked for the windows that were marked in earlier stage. component) images. T = graythresh (I) computes a global threshold T from grayscale image I, using Otsu's method [1] . B. There may be cases where the image you want to show is created within MATLAB and Image Row 0 might simply need to be associated with the smallest Y-coordinate shown on the axes. Digital image processing Image filtering can be grouped in two depending on the effects: Low pass filters (Smoothing) Low pass filtering (aka smoothing), is employed to remove high spatial frequency noise from a digital image. 4 SLIDING WINDOW TECHNIQUE A sliding window is used to mark all the windows that satisfies the edge density conditions. Single-pass methods generally have the advantage of generally being faster at coarse resolutions and are less at risk of smearing one Image Processing Toolbox matlab Image Segmentation Using K means Stack Overflow April 28th, 2019 - Use the kmeans Segmentation algorithm instead of the default kmeans algorithm provided in MATLAB Refer to this file This is the K means algorithm used for segmentation purpose By using this algorithm my program is working . g. That's the last to be calculated, and why you're getting that value when the code stops running. Let us have a look at the different image filtering methods in the subsequent paragraphs. It is very useful to go to Help\MATLAB Help in the MATLAB window if you have any questions not answered by this tutorial. We also take a look at the most popular neural network models used for different image processing tasks. MATLAB 6. the sliding window approach and the segmentation methods. Our top professionals are working in this field for the past ten years which has made them to guide students from MATLAB Tools for Signal Processing • Analysis of signals and design of filters • Signal Processing toolbox • Filter Design toolbox • Fixed-Point representation of signals • Fixed-Point toolbox Related products Wavelet, Statistics, Image Processing toolboxes System-level design Simulink and Signal Processing Blockset Nov 14, 2018 · In MATLAB, as always, there are two ways to perform any image processing algorithm, one is by directly entering the command in the editor/command window and other is by creating a GUI for the same. One is using histogram equalization, Wiener filtering and image binarization and other is using anisotropic filter for direct gray scale enhancement . After processing the image, the MATLAB code will return the processed image back to C#. In any, case before any of these, you can first calculate your A and B per pixel: A = all (yourimage Application of the sliding window algorithm in SWIMRT C. ECE 439 LECTURE SCHEDULE Image Filtering. In image processing procedures, process such as image pre-processing, segmentation and feature extraction have been discussed in detail. I see three options here: Apr 23, 2014 · I am implementing HOG for people detecting, however, I have problem on sliding window technique to detect multiple people in images. Changes that take place in images are usually performed automatically and rely on carefully designed algorithms. Then the image is undergone to segmentation using Thresholding method. Bernd Girod. kernel or convolution matrix or mask. As a sliding window methodology (described below) is used for image subsampling, the CNN gets a set of cropped images and the output is a classification stating whether the cropped image contains a pedestrian or not. Aug 01, 2011 · pls guide me to use sliding window concept in image processing for finding LBP feature of an image [Information from other posting] how to apply a 3*3 sliding window for an image and specify a method to find LBP (local binary pattern) features of an image. Jan 04, 2003 · a color image consists of three individual monochrome images, referred to as the . Prof. First, a classifier is trained on a collection of training samples spanning the object of interest for detection as one class and random objects as the other class. Conversely, you can detect homogenous blocks that lack create a sliding window to determine when a % of numbers in a sequence equal a certain value. contrast enhancement is to improve the contrast of lesions for detection using a w*w sliding window with assumption that w is large enough to contain a statistically representative distribution of the local variation of lesions. Introduction. First, a copy of the image is made and converted to grayscale. Thanks. , Kasturi, R. 5 and Octave 3. Sliding window was used to reconstruct the composite images by the conventional regridding technique and the time-resolved images with the temporal resolution of one image per heartbeat were reconstructed after the CG-HYPR MATLAB has extensive facilities for displaying vectors and matrices as graphs, as well as annotating and printing these graphs. To read an image, use the imread command. What happens is this: Notice in the last column the windows are 32x30, in the last row the windows are 12x32, and the last window (bottom-right) is 12x30. Please someone guides me to build a sliding window technique for multiple people detection in Matlab. Please Like, Comment and Share the Video among your friends. Hope this helps. One goal in image restoration is to remove the noise from the image in such a way that the original image is discernible. We have stored the binary images of all the alphabets and numbers in the sub-folder named as ‘ alpha'. Sharpening enhances the edges and fine details of an image for viewing by human beings. Image overlays » Steve on Image Processing with MATLAB . Dec 07, 2018 · Using the sliding windows method and trained CNN for detection, we created a dataset of 2300 cells annotated as T-cells and B-cells from 6 experiments and 2500 images. It increases the contrast Sliding Window Memory Buffer Architecture In the fields of image processing, feature detection, the edge detection is an important aspect. The center pixel of the structuring element, called the origin, identifies the pixel in the image being processed. 3×3 window) over an image. For example this simple kernel can be used for edge detection!!! 0. The first form takes two input images and produces an output image in which the pixel values are just those of the first image, multiplied by the values of the corresponding values in the second image. and compared their results with Object Analysis. Use rgb2gray if single-layer needed. This is commonly know as Sliding window problem or algorithm. Let’s call our input vector f and our kernel g, and say that f has length n, and g has length m. I = imread (‘image4. 1 shows insertion of the original image in ‘‘ Matlab program’’, Fig. A standard median operation is implemented by sliding a window of oddsize (e. Machine Vision. Sliding window technique compared to the binary image used as input. Datasets acquired by the segmented radial FLASH sequence were reconstructed offline by MatLab (MathWorks, Natick, MA). cancer resnet microscopy sliding-windows lung wsi medical-image-analysis pathology-image histopathology-images image. One of the barriers to playing music for recreation more advantageous to patients. 2. For the real-time data set, reconstruct with FFT, and also using a sliding window reconstruction (see Foo et al, Figure 3), or mathematically, to construct an intermediate kspaced data set (Sint (kx,ky), use data acquired for phase n, and phase n+1. JPG, and store it in an array named I. We learn about its general information and some examples will be solved using it. Dragging the mouse vertically up and down changes the brightness. Min/max image filter. Now, open the Editor window in the MATLAB, as shown in the below image, If you are not familiar with the basic terminology of Jan 24, 2012 · Without lighting information, it is difficult. The new algorithm is effective, robust against noise,independent to the initial contour, fast, and highly parallelizable. If you are a Windows user, you Project will be some application of image enhancement, restoration or coding/compression technique to digital image(s). sliding window technique in image processing matlab

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