Latest Research on Image Processing: Oct – 2019

 Latest Research on Image Processing: Oct – 2019

Two-dimensional signal and image processing

Theoretical and applications aspects of digital process for two-dimensional signals or pictures ar examined in an exceedingly textbook for advanced college man and graduate students of engineering or technology. Chapters ar dedicated to signals, systems, and therefore the Fourier transform; the z-transform; the distinct Fourier transform; finite and infinite impulse response filters; spectral estimation; the fundamental principles of image processing; image enhancement; image restoration; and image secret writing. Diagrams, graphs, sample pictures, and issues for every chapter ar provided. [1]

Microscope Image Processing

Digital image process, AN integral a part of research, is progressively necessary to the fields of drugs and research. This book provides a singular one-stop reference on the idea, technique, and applications of this technology.Written by leading consultants within the field, this book presents a singular sensible perspective of progressive magnifier image process and also the development of specialised algorithms. It contains in-depth analysis of strategies let alone the results of specific real-world experiments. magnifier Image process covers image conversion and show, object measure and classification, autofocusing, and structured illumination.Key Features:. elaborated descriptions of the many leading-edge strategies and algorithms. In-depth analysis of the strategy and experimental results, taken from real-life examples. stress on machine and recursive aspects of magnifier image process.Advanced material on geometric, morphological, and rippling image process, visible light, three-dimensional and time-lapse research, magnifier image sweetening, MultiSpectral imaging, and image knowledge managementThis book is of interest to any or all scientists, engineers, clinicians, post-graduate fellows, and graduate students operating within the fields of biology, medicine, chemistry, pharmacological medicine, and alternative connected fields. [2]

Image processing with ImageJ

Wayne Rasband of authority has created ImageJ, Associate in Nursing open supply Java-written program that’s currently at version one.31 and is employed for several imaging applications, as well as people who that span the gamut from skin analysis to neurobiology. ImageJ is within the property right and runs on any software package (OS). ImageJ is simple to use and might do several imaging manipulations. a really giant and knowledgeable cluster makes up the user community for ImageJ. Topics lined square measure imaging abilities; cross platform; image formats support as of Gregorian calendar month 2004; extensions, as well as macros and plug-ins; and imaging library. authority reports tens of thousands of downloads at a rate of concerning twenty four,000 per month presently. ImageJ will browse most of the wide used and important formats employed in medical specialty pictures. Manipulations supported square measure read/write of image files and operations on separate pixels, image regions, entire pictures, and volumes (stacks in ImageJ). [3]

Diffusion Tensor Imaging of the Kidney: Design and Evaluation of a Reliable Processing Pipeline

Diffusion tensor imaging (DTI) is especially appropriate for urinary organ studies because of tubules, collector ducts and blood vessels within the medulla that turn out spatially restricted diffusion of water molecules, therefore reflective the high grade of property detectable by DTI. urinary organ DTI remains a difficult technique wherever the off-resonance susceptibleness artefacts and subject motion will severely have an effect on the dependableness of results. The aim of this study is to style a reliable process pipeline by assessing totally different image process approaches in terms of dependableness and image artefacts correction. The results of 4 totally different process pipelines (eddy: correction of eddy-currents and motion between DTI volume; eddy-s2v: eddy and at intervals DTI volume motion correction; topup: eddy and geometric distortion correction; topup-s2v: topup and at intervals DTI volume motion correction) square measure compared in terms of dependableness by test-retest analysis in fourteen healthy subjects. [4]

Classification of Soya Beans Based Image Processing Techniques and Artificial Neural Network

The benefits of victimization technology in agriculture can’t be overemphasised owing to its impact that ends up in a rise within the quality and amount of crops made, minimising value of farming, and providing suggestions for prompt action among others. historically, to grasp the state of Glycine max beans, farmers deem observation to notice the amendment in color of the leaves therefore on give acceptable action to the crop. This method can’t be totally reliable as color is subjective to human impression; and failure to act once there area unit changes within the state of the Glycine max beans particularly once tormented by diseases will scale back the expected yield. The goal of this study is to classify Glycine max beans leaves into numerous classes like healthy, unhealthy/disease, ripe not prepared for harvest and ripe prepared for harvest in order that prompt action may be taken. [5]


[1] Lim, J.S., 1990. Two-dimensional signal and image processing. Englewood Cliffs, NJ, Prentice Hall, 1990, 710 p. (Web Link)

[2] Wu, Q., Merchant, F. and Castleman, K., 2008. Microscope image processing. Academic Press, Inc.. (Web Link)

[3] Abràmoff, M.D., Magalhães, P.J. and Ram, S.J., 2004. Image processing with ImageJ. Biophotonics international, 11(7), (Web Link)

[4] Diffusion Tensor Imaging of the Kidney: Design and Evaluation of a Reliable Processing Pipeline
Pasquale Borrelli, Carlo Cavaliere, Luca Basso, Andrea Soricelli, Marco Salvatore & Marco Aiello
Scientific Reports volume 9, Article number: 12789 (2019) (Web Link)

[5] Abdulhamid, U., Daniel, S. and Babawuro, U. (2018) “Classification of Soya Beans Based Image Processing Techniques and Artificial Neural Network”, Journal of Advances in Mathematics and Computer Science, 26(6), (Web Link)


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