Study about Performance Analysis of Image Enhancement Techniques for Optical Character Recognition (OCR) | Chapter 8 | Theory and Applications of Engineering Research Vol. 3

Image enhancement is one crucial component of the image processing sector, which allows upgrading the image class to construct the consequential image further valuable than the original.

Digital image processing is an indispensable domain in the present era. Image enhancement is a crucial phase in image processing that aims to produce a more desirable effect than the original image.

The clarity of an image is influenced by various factors, including the capturing device, environmental conditions, and illumination.

Numerous image enhancement techniques have been developed to restore image information. Image enhancement methods offer a range of options for improving the quality of images. The choice of these methods is influenced by various factors such as image input, display instrument, and task requirements. It is renowned that image processing system is superior whenever the performance of the image enhancement routine is high. This study provides an overview of image enhancement perception and evaluates commonly used algorithms using MATLAB R2014a based on four assessment parameters. The edge adaptive hybrid filter was found to be superior. For future vocation one could discover an innovative image enrichment method, amendment in presenting techniques with healthier truth or suitable amalgamation of image augmentation schemes.

Author(s) Details:

M. S. Sonawane,
SGBAU, Amravati (M.S.), India.

C. A. Dhawale,
P. R. Pote College of Engineering and Management, Amravati (M.S.), India.

Please see the link here: https://stm.bookpi.org/TAER-V3/article/view/13060

Experiments on the Interpolation of the Histogramed MR Brain Images for Resolution Enhancement | Chapter 10 | Recent Developments in Engineering Research Vol.2

 

Magnetic resonance imaging (MRI) is an incredible testing method which provides appropriate
anatomical images of the body. For the diagnosis, high resolution MR images are essential to extract
the detailed information about the diseases. However, with the measured MR images it’s a
challenging issue in extracting the detailed information associated to disease for the posterior analysis
or treatment. Usually to improve the resolution of the MR image, histogram equalization process has
to be applied. In this paper, interpolation method is applied to improve the resolution of MR brain
images for the histogram-ed images. And for the assessment of the skillfulness of introduced method,
performance metrics such as peak signal to noise ratio (PSNR) and absolute mean brightness error
(AMBE) are measured. The peak of signal for the enhanced images through interpolation will be much better and may have the good variation to the mean brightness error. With this there can be potential to the artificial intelligence for better diagnosis in complex decisive instances.

Author(s) Details

Mr. A. Charles Stud
Research Scholar, ECE Department, JNT University Anantapur, Ananthapuramu, Andhra Pradesh, India.

Dr. N. Ramamurthy
Professor, ECE Department, G. Pullaiah College of Engineering & Technology, Kurnool, Andhra Pradesh, India.

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