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Image processing applications

Applications of Digital Image Processing 1) Image sharpening and restoration. It refers to the process in which we can modify the look and feel of an image. It... 2) Medical Field. There are several applications under medical field which depends on the functioning of digital image... 3) Robot. Applications of Digital Image Processing Image sharpening and restoration Medical field Remote sensing Transmission and encoding Machine/Robot vision Color processing Pattern recognition Video processing Microscopic Imaging Other Photo Studio Ultimate 2021 is a one-stop photo management and post-processing tool for Windows. It comes with everything you need to handle your files, like categories, keywords, face detection, ratings, color labels, metadata, geolocation, and more Filters are an interesting application of Image processing. 3

Applications of Digital Image Processing - Javatpoin

  1. The Best Photo Editing Software for 2021. Whether you're a casual smartphone shooter or a professional using an SLR, software can get the most out of your images
  2. Image processing has numerous applications in most human activities, from medicine (Papour et al., 2015) or security (Zhou et al., 2015) to astronomy (Wang et al., 2014) or transportation (Zeng et al., 2015) and quality control (Jeong and Lee, 2015)
  3. Nowadays, Image processing is normally used by a wide range of applications and in different types of electronics like computers, digital cameras, mobile phones, etc. The image properties can be changed with the least investment such as contrast enhancement, borders detection, intensity measurement & apply different mathematical functions to enhance the imagery

Android based Image Processing Projects. Android Application for Face Recognition This report presents all the processes I use to program an android application of face recognition. At the beginning, I used the android API, after a long study of the android litterature, to make this application. Because of devices problem, I had t Artificial intelligence has many applications in image processing. For example: developing computer aided diagnosis systems that help doctors in interpreting images of X-ray , MRI e.t.c and then highlighting conspicuous section to be examined by the doctor. Signal processing. Signal processing is an umbrella and image processing lies under it Image Processing Toolbox™ provides a comprehensive set of reference-standard algorithms and workflow apps for image processing, analysis, visualization, and algorithm development. You can perform image segmentation, image enhancement, noise reduction, geometric transformations, image registration, and 3D image processing

Maple is a remarkably flexible tool to use for analyzing and manipulating images. Maple's interactive command-driven environment, document interface with inl.. Image processing is a method to perform some operations on an image, in order to get an enhanced image or to extract some useful information from it. It is a type of signal processing in which input is an image and output may be image or characteristics/features associated with that image

Once a customer decides on a model, their dimensions could be determined via an image processing system (machine vision system). This might take the form of a small changing room with four cameras to take a picture of each side of the body. Software handles the measurements and the subsequence cutting pattern for production It is one of the most widely used tools for computer vision and image processing tasks. It is used in various applications such as face detection, video capturing, tracking moving objects, object disclosure, nowadays in Covid applications such as face mask detection, social distancing, and many more Digital image processing is the use of a digital computer to process digital images through an algorithm. As a subcategory or field of digital signal processing, digital image processing has many advantages over analog image processing.It allows a much wider range of algorithms to be applied to the input data and can avoid problems such as the build-up of noise and distortion during processing Complex image processing algorithms are used in applications ranging from detection of soldiers or vehicles, to missile guidance and object recognition and reconnaissance. Biometric techniques including fingerprinting, face, iris and hand recognition are being used extensively in law enforcement and security The major applications of imaging in the radio band are in medicine and astronomy. In medicine radio waves are used in magnetic resonance imaging (MRI). This technique places a patient in a powerful magnet and passes radio waves through his or her body in short pulses

Image Processing Onramp Use MATLAB ® and Simulink ® to gain insight into your image and video data, develop algorithms, and explore implementation tradeoffs. Design vision solutions with a comprehensive set of reference-standard algorithms for image processing, computer vision, and deep learning IMAGE ENHANCEMENT - It is amongst the simplest and most appealing in areas of Image Processing it is also used to extract some hidden details from an image and is subjective. 3. IMAGE RESTORATION - It also deals with appealing of an image but it is objective (Restoration is based on mathematical or probabilistic model or image degradation). 4

Image Processing is a subset of Computer Vision. Computer Vision is a superset of Image Processing. Examples of some Image Processing applications are- Rescaling image (Digital Zoom), Correcting illumination, Changing tones etc. Examples of some Computer Vision applications are- Object detection, Face detection, Hand writing recognition etc Medical imaging is the procedure used to attain images of the body parts for medical uses in order to identify or study diseases. There are millions of imaging procedures done every week worldwide. Medical imaging is developing rapidly due to developments in image processing techniques including image recognition, analysis, and enhancement However, in many image processing applications, the XY location of the pixels themselves is crucial information. A simple example of this might be, set every even column of pixels to white and every odd to black. How could you do this with a one dimensional pixel array? How do you know what column or row any given pixel is in

Applications and Usage - Tutorialspoin

  1. Image Processing is used to enhance the image quality through techniques like image sharpening and restoration. The images can be altered to achieve the desired results. Digital Image Processing finds its application in the medical field for gamma-ray imaging, PET Scan, X-ray imaging, UV imaging. It is used for transmission and encoding
  2. Image Processing -Image processing is one of the best and most interesting domain. In this domain basically you will start playing with your images in order to understand them. So here we use many many techniques which includes feature extraction as well and algorithms to detect features such as shaped, edges, or motion in a digital image or.
  3. Image processing is a method to perform some operations on an image, in order to get an enhanced image or to extract some useful information from it. Well, don't be overwhelmed by all those technical terms, we will help you with the fundamentals
  4. Medical Image Processing: Techniques and Applications meets this challenge and provides an enduring bridge in the ever expanding field of medical imaging. It serves as an authoritative resource and self-study guide explaining sophisticated techniques of quantitative image analysis, with a focus on medical applications
  5. Lec 1 : Introduction to Digital Image Processing: Download: 2: Lec 2 : Introduction to Computer Vision: Download: 3: Lec 3 : Introduction to Computer Vision and Basic Concepts of Image Formation: Download: 4: Lec 4 : Shape From Shading: Download: 5: Lec 5 : Image Formation: Geometric Camera Models - I: Download: 6: Lec 6 : Image Formation: Geometric Camera Model - II: Download:
  6. Image Processing with ImageJ is a practical book that will guide you from the most basic analysis techniques to the fine details of implementing new functionalities through the ImageJ plugin system, all of it through the use of examples and practical cases

JRTIP bridges the gap between the theory and practice of image processing. Covers real-time image processing systems and algorithms for industrial, medical, consumer electronics, portable and embedded device applications. Presents practical, low-cost, and real-time architectures for image processing systems as well as tools, simulation and. Hybrid Image of a Cat and a Dog. Rating: Maple Document. Samir Khan. A measure of how popular the application is. Includes number of downloads, views, average rating and age. Read more about popularity. Removal of Periodic and Salt & Pepper Noise from an Image An Image Processing Application in C++ Introduction. Some basic image processing functions involve manipulation of the pixels using filters or histogram based... Background. The application, called Imagr (spelled without an e for historical reasons), is built as a MFC... MDI Advantages. Designing.

scikit-image is an image processing library that implements algorithms and utilities for use in research, education, and industry applications. It is released under the liberal Modified BSD open source license, provides a well-documented API in the Python programming language, and is developed by an active, international team of collaborators Components of an Image Processing System 5. Mass Storage Capability Mass storage capability is a must in a image processing applications. And image of sized 1024 * 1024 pixels requires one megabyte of storage space if the image is not compressed. Digital storage for image processing applications falls into three principal categories: 1 Image Processing with Python Python is a high level programming language which has easy to code syntax and offers packages for wide range of applications including nu... LIKE IMAGE PROCESSING Support this blog by leaving your valuable comments and a like on Facebook Fan Page. THANKS FOR READING An image processing application programmed in c++. Contribute to Yuhala/image-processing-cpp development by creating an account on GitHub Morphological image processing is a collection of non-linear operations related to the shape or morphology of features in an image. According to Wikipedia, morphological operations rely only on the relative ordering of pixel values, not on their numerical values, and therefore are especially suited to the processing of binary images.

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Digital Image Processing Applications Image Processing

Application. The application uses the basic Windows Forms application. I have handled the images with a separate class called ImageHandler in which all the image related operations are done including Saving, Graphics related operations. The Functionality includes getting image information, zooming, color filtering, brightening, contrasting. Biomedical image processing is a very broad field; it covers biomedical signal gathering, image forming, picture processing, and image display to medical diagnosis based on features extracted from images. This article reviews this topic in both its fundamentals and applications. In its fundamentals, Building Image Processing Applications Using scikit-image. By Janani Ravi. In this course, you'll explore the scikit-image Python library which allows you to apply sophisticated image processing techniques to images and to quickly extract important insights or pre-process images for input to machine learning models. Start a FREE 10-day trial

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IDRISI is a combined GIS and image processing system that offers advanced capabilities in both areas. Because of the extreme importance of remote sensing as a data input to GIS, it has become necessary for GIS analysts (particularly those involved in natural resource applications) to gain a strong familiarity with IPS. Consequently, this chap Image processing is done for various purposes, including the retrieval of specific information from an image, image recognition, image clarity or enhancement and pattern measurement. Types of image processing can also be separated into digital image processing, where programs work on a digital array of pixels, and analog image processing, where. Remote sensing data provides much essential and critical information for monitoring many applications such as image fusion, change detection, and land cover classification. Remote sensing is an important technique to obtain information relating to the Rarth's resources and environment. Satellite Image Processing, Pre-Sales Presentations.. Image classification on Azure. This scenario is relevant for businesses that need to process images. Potential applications include classifying images for a fashion website, analyzing text and images for insurance claims, or understanding telemetry data from game screenshots. Traditionally, companies would need to develop expertise in machine.

Tensor signal processing is an emerging field with important applications to computer vision and image processing. However, tensor applications and tensor-processing tools arise from very different areas, and these advances are too often kept within the areas of knowledge where they were first employed Signal Processing for Media Applications. The Signal Processing for Media Applications (Sigmedia) Group is a research group in the Department of Electronic and Electrical Engineering at Trinity College Dublin.. Research. We explore problems that involve visual or audio digital media The LEADTOOLS Image Processing application for Android allows you to apply effects to images loaded from your computer. Here are some of the image processing filters that can be applied to images using this app: • Color: Adaptive Contrast, Adjust Tint, Auto Binary, Auto Color Level, Blur Detection, Change Hue, Change Saturation, Color. Image Processing Application in modern Systems makes them smart, interactive integrating features going sometimes beyond human intelligence. The international Image Processing Applications and Systems conference aims at grouping from all over the world challenging researchers, innovators, academicians, and practitioners in image processing.

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image interpolation and a comprehensive new section summarizing the principal mathematical tools used in the book. Instead of presenting dry mathematical concepts one after the other, however, we took this opportu-nity to bring into Chapter 2 a number of image processing applications that were scattered throughout the book Image Processing and Analysis for Life Scientists. Basic image analysis for life scientists with a non-engineering background. The main goal is to teach how to address and solve scientific questions by state of the art image analysis strategies. There is one session available: Starts Jun 28. 10,393 already enrolled

Image Processing - an overview ScienceDirect Topic

In digital image processing and computer vision, image segmentation is the process of partitioning a digital image into multiple segments (sets of pixels, also known as image objects).The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze Moreover, the complex weighted summation is executed in an efficient way with a proper design of Mm-CNN cell circuits. The proposed Mm-CNN has several merits, such as compactness, nonvolatility, versatility, and programmability of synaptic weights. Its performance in several image processing applications is illustrated through simulations Here, in addition to reviewing some of the critical image processing applications that quantum mechanics have targeted, such as denoising, edge detection, image storage, retrieval, and compression, this study will also highlight the complexities in transitioning from the classical to the quantum domain

DOI: 10.1155/2010/432972 Corpus ID: 62140221. Advanced Image Processing for Defense and Security Applications @article{Du2011AdvancedIP, title={Advanced Image Processing for Defense and Security Applications}, author={ElizaYingzi Du and R. Ives and A. V. Van Nevel and Jinhua She}, journal={EURASIP Journal on Advances in Signal Processing}, year={2011}, volume={2010}, pages={1} Digital Image Processing (DIP) is a software which is used to manipulate the digital images by the use of computer system. It is also used to enhance the images, to get some important information from it. For example: Adobe Photoshop, MATLAB, etc. It is also used in the conversion of signals from an image sensor into the digital images Tutorial about the basic operations of Image Processing software that is ENVI. In this video all the tabs of envi are described in detail and the working of. Image Processing or more specifically, Digital Image Processing is a process by which a digital image is processed using a set of algorithms. It involves a simple level task like noise removal to common tasks like identifying objects, person, text etc., to more complicated tasks like image classifications, emotion detection, anomaly detection, segmentation etc Applications. Xilinx solutions enable smarter, connected, and differentiated systems, integrating the highest levels of software-based intelligence with hardware optimization and any-to-any connectivity

Boost content discoverability, automate text extraction, analyse video in real time and create products that more people can use by embedding cloud vision capabilities in your apps with Computer Vision, part of Azure Cognitive Services. Use visual data processing to label content with objects and concepts, extract text, generate image. The Image Processing Applications Laboratory (IPALab) at Arizona State University addresses current and important image processing problems in a variety of different fields. Ongoing research at IPALab includes projects that are biomedical, industrial, and military in nature. Our ultimate goal is to improve human quality of life through the.

Image processing in neuroimaging applications . Image processing is a fundamental part of analysis. This lesson is meant to unpack some of the fundamental algorithms in the processing of MRI images: detrending, segmentation and registration. The template we use is based on the lesson template used in Data Carpentry and Software Carpentry workshops Image processing tools for dental applications. Mol A (1). (1)Department of Diagnostic Sciences and General Dentistry, University of North Carolina at Chapel Hill, USA. Digital image processing has seen a wide variety of applications in dental radiography. Examples of operations from any of the fundamental classes can be found in the literature. Development of specialized imaging applications. Document segmentation, lines identification and other image analysis tools are core of form processing application. Low level image processing tools like morphological, filters, binarization, scaling, etc. used to build specialized document processing tools eBook ISBN 978-3-662-04186-4. Series ISSN 1612-1457. Edition Number 1. Number of Pages XX, 355. Number of Illustrations 50 b/w illustrations, 82 illustrations in colour. Topics Image Processing and Computer Vision. Optics, Lasers, Photonics, Optical Devices. Computer Applications. Signal, Image and Speech Processing RawTherapee is another cross-platform, free and open-source RAW image processing application supporting different image editing operations and a large number of file handling. Along with the usual RAW image files, it supports some less common types such as X-Trans, Foveon, and Pentax Pixel Shift

Image Processing Projects using MATLAB, Python & Androi

Image Processing (which includes Digital Image Processing Projects, Medical Image Processing Projects and so on) for Final Year Engineering Students with Free PDF Reports, Ideas & Topics with Abstracts & Source Code Downloads in Matlab, Java, C etc. This technique is widely used in various applications like Continue reading. As optics, imaging sensors, and computational technology advanced, image processing has become more commonly used in many different areas. Some areas of application of digital image processing include image enhancement for better human perception, image compression and transmission, as well as image representation for automatic machine perception Professor: Dr. Scott E Umbaugh Office: Engineering Building, Room EB3037 Phone: 650-2524, 2948 e-mail: sumbaug@siue.edu Textbook: Digital Image Processing and Analysis: Application with MATLAB and CVIPtools, 3 rd Edition, SE Umbaugh, Taylor&Francis /CRC Press, 2018 Prerequisite: ECE 351 and programming experience, or consent of instructor Class Format: Two lectures and 1 lab/homework per week. In medical applications, we have X-ray image processing, projection images of transaxial tomography, radiology, nuclear magnetic resonance (NMR) and ultrasonic scanning. Some methods of acquisition and transmission can generate noise in an image. The median filter is an image processing technique used to remove them or reduce their effects: for. Image processing has been proved to be effective tool for analysis in various fields and applications. Agriculture sector where the parameters like canopy, yield, quality of product were the important measures from the farmers' point of view. Many times expert advice may not be affordable, majority times the availability of expert and their services may consume time

ON1 is the developer of Photo RAW 2019, a dead-serious Lightroom contender sporting a powerful Raw processor, image editor, and DAM (digital asset management) system. Alien Skin Software was also founded in 1993 by Jeff Butterworth (joined soon thereafter by Finley Lee), on the other side of the country in Raleigh, North Carolina SightLine Applications is the market leader in onboard video processing. Founded in 2007, we are a team of embedded systems developers focused on providing a continuously improved set of video processing functions. At SightLine, we believe experience matters and can proudly state that our processors have over a million flight hours

12. Occlusion is the one which blocks our view. In the image shown here, we can easily see the people in the front row. But the second row is partly visible and third row is much less visible. Here, we say that second row is partly occluded by first row, and third row is occluded by first and second rows Matrix Operations for Image Processing Paul Haeberli Nov 1993 Introduction. Four by four matrices are commonly used to transform geometry for 3D rendering. These matrices may also be used to transform RGB colors, to scale RGB colors, and to control hue, saturation and contrast The research of computer vision, imaging processing and pattern recognition has made substantial progress during the past several decades. Also, medical imaging has attracted increasing attention in recent years due to its vital component in healthcare applications The MIPAV (Medical Image Processing, Analysis, and Visualization) application enables quantitative analysis and visualization of medical images of numerous modalities such as PET, MRI, CT, or microscopy. Using MIPAV's standard user-interface and analysis tools, researchers at remote sites (via the internet) can easily share research data and.

300+ Image Processing Projects For Engineering Students

Detailed Description. This module includes image-processing functions. Generated on Sun Jun 27 2021 02:14:24 for OpenCV by 1.8.13 1.8.1 The Large Scale Visual Recognition Challenge (ILSVRC) is an annual competition in which teams compete for the best performance on a range of computer vision tasks on data drawn from the ImageNet database.Many important advancements in image classification have come from papers published on or about tasks from this challenge, most notably early papers on the image classification task This is not just an application for the hearing impaired, but also in generating human readable text for image and video data that can be searched, such as on the web. Below are 3 examples of deep learning for caption generation: Generating captions for photographs. Show, Attend and Tell: Neural Image Caption Generation with Visual Attention, 2016 Introduction This application note describes the 1080p60 camera image processing reference design that showcases various features of the ZVIK, provides a working camera image processing example design, and introduces several Xilinx video IP cores. Video input is generated by the VITA-2000 image sensor from ON Semiconductor, which i

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Digital Image Processing Introduction - Tutorialspoin

Emerging Trends in Image Processing, Computer Vision, and Pattern Recognition discusses the latest in trends in imaging science which at its core consists of three intertwined computer science fields, namely: Image Processing, Computer Vision, and Pattern Recognition. There is significant renewed interest in each of these three fields fueled by Big Data and Data Analytic initiatives including. Microsemi's SoCs and FPGAs with their unique differentiating factors provide an ideal solution for medical applications such as Human Machine Interface (HMI), displays, frame grabbing, video capture and Image processing. Microsemi FPGA Differentiating Factors in Medical Imaging. Reliability with Non-Volatile Memory Digital image processing and analysis is a field that continues to experience rapid growth, with applications in many facets of our lives. Areas such as medicine, agriculture, manufacturing, transportation, communication systems, and space exploration are just a few of the application areas imaging applications, such as processing of satellite images, the trend continues toward miniaturizing and blending of general-purpose small computers with specialized image processing hardware. Figure 3 shows the basic components comprising a typical general-purpose system used for digital image processing

Nonetheless, the RGB model has been wildly successful and is frequently used in sensor and image-processing applications. In my opinion, the RGB model is, overall, quite intuitive. The key to understanding RGB image processing is recognizing that an RGB image is simply a composite of three independent grayscale images that correspond to the. Image Processing with MATLAB®: Applications in Medicine and Biology explains complex, theory-laden topics in image processing through examples and MATLAB® algorithms. It describes classical as well emerging areas in image processing and analysis. Providing many unique MATLAB codes and functions throughout, the book covers the theory of probability and statistics, two-dimensional fast Fourier. With the fast computers and signal processors available in the 2000s, digital image processing has become the most common form of image processing, and is generally used because it is not only the most versatile method, but also the cheapest. Digital image processing technology for medical applications was inducted into the Space Foundation Spac ImageProcess.zip. This application explains basic concepts of image processing including brightening, converting to gray and adding notes to an image using System.Drawing.Imaging namespace classes. Following code shows how to display an image in a picture box. The screen shot above shows an image before and after increasing brightness Darkroom. Darkroom is a powerful and robust photo editing app that is perfect for your iPad, and even your iPhone. Regardless of the device that you're using, Darkroom is perfectly tuned to make the most of the screen estate that it has to work with. You get RAW support, Portrait mode editing, custom filters, hashtag managers, content-aware.

Image Processing Toolbox - MATLA

Therefore, processing remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. In recent decades, this area has attracted a lot of research interest, and significant progress has been made. Many advances can be seen concerning image processing. darktable is an open source photography workflow application and raw developer. A virtual lighttable and darkroom for photographers. It manages your digital negatives in a database, lets you view them through a zoomable lighttable and enables you to develop raw images and enhance them The next sections give a brief description of FFT and its advantages and application in image processing, implementation of the algorithm in DirectX10 and conclusions. Fast Fourier Transform Fourier Transform decomposes an image into its real and imaginary components which is a representation of the image in the frequency domain A GPU performs the same function, but in reverse, for image processing applications. Instead of starting with the conditions within a video game and attempting to render them onto a screen with millions of pixels, in machine vision, millions of pixels are processed down to help software interpret and understand the images • Image processing is a natural fit for data parallel processing - Pixels can be mapped directly to threads - Lots of data is shared between pixels • Advantages of CUDA vs. pixel shader-based image processing • CUDA supports sharing image data with OpenGL and Direct3D applications introductio

Applications in Image Processing - YouTub

How Application-Aware Processing Works. If you enable application-aware processing in job settings, Veeam Backup & Replication performs the following operations as a part of the backup or replication process: Veeam Backup & Replication deploys the non-persistent runtime components or, if necessary, persistent agent components on the VM and detects if the VM runs any of the supported applications Image and Video Processing is an active area of research due to its potential applications for solving real-world problems. Integrating computational intelligence to analyze and interpret information from image and video technologies is an essential step to processing and applying multimedia data

1. Introduction to image processing Digital Image Processin

VJML1EYOCB7Z // Doc ~ MATLAB Applications succinctly - image processing and GUI design articles MATLAB Applications succinctly - image processing and GUI design articles Filesize: 8.88 MB Reviews I just started out reading this ebook. It is rally exciting throgh reading through time. Once you begin to read the book, it is extremel Home » Courses » IT & Software » [FREE] Digital Image Processing: Operations and Applications. 0 [FREE] Digital Image Processing: Operations and Applications. smallacademy June 28, 2020 0. What you Will learn ? Understand the fundamentals of Image Processing, Image Enhancement, Image Segmentation.. High Speed Image Processing Using FPGA Processor. client is an OEM in the inspection industry and they manufacture high-speed sorting and gradin g machines for industrial applications. The end.

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Image Processing in Industry 4

In this module we cover the important topic of image and video enhancement, i.e., the problem of improving the appearance or usefulness of an image or video. Topics include: point-wise intensity transformation, histogram processing, linear and non-linear noise smoothing, sharpening, homomorphic filtering, pseudo-coloring, and video enhancement Natural language processing tools can help businesses analyze data and discover insights, automate time-consuming processes, and help them gain a competitive advantage. Let's take a look at 11 of the most interesting applications of natural language processing in business: Sentiment Analysis. Text Classification. Chatbots & Virtual Assistants You can find several Three Dimensional Image Processing (3dip) And Applications Atilla Baskurt essay writing services online and Three Dimensional Image Processing (3dip) And Applications Atilla Baskurt hire a cheap essay writer for your essay. However, while hiring a cheap essay writer, you have to make sure that you contact a reliable and professional essay writing service like. Finds and recognizes both CMC-7 and E-13B fonts in images; Passport Reader. Recognizes and parses passport information in images. Develop applications for industries and government agencies that process MRP and MRTD. Extract fields regardless of image resolution, scale, and other characteristics; World-class accuracy and spee Image Processing and Analysis. Many image processing and analysis techniques have been developed to aid the interpretation of remote sensing images and to extract as much information as possible from the images. The choice of specific techniques or algorithms to use depends on the goals of each individual project

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