BEST IMAGE PROCESSING TOOLS TO EXPECT in 2023 – Tutors India

1. TOP 13 IMAGE PROCESSING TOOLSTOEXPECT IN2023 AnAcademicpresentationby Dr.NancyAgnes,Head,TechnicalOperations,TutorsIndia Groupwww.tutorsindia.com Email:info@tutorsindia.com

2. INTRODUCTION As the name suggests, processing an image entails a numberofstepsbefore wereachourgoal. The end result may be an image or a feature that is similarto thatimage. Additional research and decision-making can be done usingthisinformation.Belowarethebestimage processingtoolsusedinmachine learning.

3. Figure1:BestimageProcessingToolsUsedinMachineLearning

4. OPENCV A popular library that is simple to use is multi-platform. It flawlessly integrates withC++ and Pythonand provides all theessentialmethods andalgorithmsneeded to complete a few image and video processing tasks(Salvi et al.,2021) . MATLAB Since it allows for rapid prototyping, Matlab is a great tool forcreatingimageprocessingsystemsandis extensively used in research. Another interesting point is howmuchshorterMatlabcodeisthanC++code,making it simpler to read and troubleshoot. It addresses errors prior toexecution byoffering anumber ofoptions to expedite the process.

5. CUDA NVIDIA, which is fast, highly efficient, and easy to program, serves as the foundation for parallelcomputing.ItgivesoutstandingperformancebyutilizingGPUpower.Incorporated into its toolset is the NVIDIA Performance Primitives library, which offers a variety of image, signal, andvideoprocessingtechniques(Abdulrahmanet al.,2021) . TENSORFLOW The most used deep learning and machine learning library currently in use is this one. It quicklygainedpopularityandsurpassedcompetinglibrariesduetotheeaseofuseofthe API.ThedifferentialprogramminganddatastreamlibraryTensorFlowisopen-sourceand free.Itisasymbolicmathlibrarythatisutilizedbyneuralnetworksandothermachine learning applications.

6. TensorFlow2.0encouragestheuseofpre-builtmodelsforavarietyofapplications, includingobjectdetection,reinforcementlearning,voiceandpicturerecognition.These reference models give you the ability to employ certain best business practices and act as a platformfor creatingyour superior solutions(Reinkeet al.,2021) . SIMPLECV A system for creatingcomputer vision applicationsis called SimpleCV. It provides access to severalcomputervisiontechnologiesonanyOpenCV,pygame,andotherplatforms.You need this program if all you need to do is finish the task and you don't want to learn all the specificsofimageprocessing.SimpleCVisthebestoptionifrapidprototypingisrequired.

7. PYTORCH Machine learning open-source platform PyTorch. The process is designed to accelerate the transition from a research prototype to commercial development. Easyproductiontransition Performanceenhancementwithdistributedadaptivelearning Thrivingecosystemfortools andlibraries Excellentsupportfortheprimarycloudplatforms Optimizationmodulesandindependentdifferentiation

8. KERAS Tensorflow, Theano, and CNTK are just a few of the libraries that Keras, a deep learning Python library, includes. In comparison to competitors like Scikit-learn and PyTorch, Keras hasan advantagebecause it isdeveloped on topof Tensorflow. Any of the following can be utilized with Keras: TensorFlow, Microsoft Cognitive Toolkit, Theano, or PlaidML. It is made for quick deep neural network experimentation and places a premiumonconvenience,quantitativequality,andextensibility.Kerasadherestobest practices for decreasing cognitive load by offering stable and basic APIs and limiting the amountof userinvolvement requiredfor typicaluse cases(Zhang, 2021).

9. THEANO Theano is a swift Python numerical library that may be utilized with a CPU or GPU. At the Canadian University of Montreal, it was created by the LISA group, which is now knownasMILA.Theano isadevelopingcompilerfor controlling andassessingmathematicalexpressions, particularlythoseusingmatrixvalues. EMGUCV EmguCVisaplatform-agnostic imageprocessing program. a Net extension for OpenCV. IronPython, C#, VB, and VC++ are among the.NET compatible languages that it supports. It runs on Windows, Linux, Mac OS, iOS, and Android platforms. It is also compatible with Visual Studio,XamarinStudio, and Unity.

10. GPUIMAGE It is an OpenGL ES 2.0-based framework that enables the addition of GPU-accelerated effectsandchannelstothelive-actvideoside,stillimages,andmotionpictures.Tosetup andkeeprunningcustomchannels onaGPU,asignificantamount ofcodemustbe developed. YOLO "You Just Look Once" (YOLO), an approach to object detection, was created with real-time processing inmind.Joseph RedmonandAliFarhadi,researchers attheUniversity of Washington, created the advanced real-time object detection technology known as YOLO. Their method uses a neural network to divide the entire image into districts with the found items,leavingimprintsof thosedistricts onthe grid(Dinget al.,2021) .

11. VXL VXL is a collection of open-source C++ libraries. This image editing application has the ability to open, save, and edit photos in a variety of frequently used file types, including huge images. Geometryforpoints,curves,andotherfundamentalobjectsin1,2,or3 dimensions. Cameraphysics regainingstabilityfollowingmovement Implementingagraphicaluserinterface 3D topologypictures

12. BOOFCV BoofCV is an open-source Java framework with an Apache 2.0 license that may be used for bothprofessional andacademicreal-timerobotics andcomputervisionapplications. Structure-from-motion,featuretracking,cameraalignment, andefficientlow-level image processingtechniques are some ofitsfeatures(C et al.,2022) .

13. CONCLUSION Deep learning's use of Broadway lingo and advances in image processing are changing the world. This is just the beginning of the learning process because scientists are constantlycreatingbettertechniques tooptimizethe entire field of image processing.All the tasks you must accomplish can be completed using a variety of image processing techniques. Looking to write a research proposal on image processing techniques? At tutorsindia, Our expertise will assist you fromidentifyingproblem tothe researchsolutions

14. REFERENCES Abdulrahman, A.A., Rasheed, M. & Shihab, S. (2021). The Analytic of Image Processing Smoothing Spaces Using Wavelet.JournalofPhysics:ConferenceSeries.[Online].1879(2).pp.022118.Availablefrom: https://iopscience.iop.org/article/10.1088/1742-6596/1879/2/022118. C,D.,N,N.U.,Maddikunta,P.K.R.,Gadekallu,T.R.,Iwendi,C.,Wei,C.&Xin,Q.(2022).Identificationof malnutrition and prediction of BMI from facial images using real‐time image processing and machine learning. IET Image Processing. [Online]. 16 (3). pp. 647–658. Available from: https://onlinelibrary.wiley.com/doi/10.1049/ipr2.12222. Ding,K.,Ma,K.,Wang,S.&Simoncelli,E.P.(2021).Comparisonoffull-referenceimagequalitymodelsfor optimization of image processing systems. International Journal of Computer Vision. [Online]. 129 (4). pp. 1258– 1281.Available from:https://link.springer.com/article/10.1007/s11263-020-01419-7. Reinke,A.,Tizabi,M.D.,Sudre,C.H.,Eisenmann,M.,Radsch,T.,Baumgartner,M.,Acion,L.,Antonelli,M.,Arbel, T.&Bakas,S.(2021).Commonlimitationsofimageprocessingmetrics:Apicturestory.arXivpreprint arXiv:2104.05642.[Online]. Available from:https://arxiv.org/abs/2104.05642. Salvi, M., Acharya, U.R., Molinari, F. & Meiburger, K.M. (2021). The impact of pre- and post-image processing techniquesondeeplearningframeworks:Acomprehensivereviewfordigitalpathologyimageanalysis.Computers inBiologyandMedicine.[Online].128.pp.104129.Availablefrom: https://linkinghub.elsevier.com/retrieve/pii/S0010482520304601. Zhang,Y.-J.(2021).ImageEngineering.In:HandbookofImageEngineering.[Online].Singapore:Springer Singapore,pp. 55–83.Available from:http://link.springer.com/10.1007/978-981-15-5873-3_2.

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