TOP 13 IMAGE PROCESSING TOOLS TO EXPECT 2023
Introduction
As
the name suggests, processing an image entails a number of steps before we
reach our goal. The end result may be an image or a feature that is similar to
that image. Additional research and decision-making can be done using this
information. Below are the best image processing tools used in machine learning.
OpenCV
A
popular library that is simple to use is multi-platform. It flawlessly
integrates with C++
and Python and
provides all the essential methods and algorithms needed to complete a few
image and video processing tasks (Salvi
et al., 2021).
Matlab
CUDA
NVIDIA,
which is fast, highly efficient, and easy to program, serves as the foundation
for parallel computing. It gives outstanding performance by utilizing GPU
power. Incorporated into its toolset is the NVIDIA Performance Primitives
library, which offers a variety of image, signal, and video processing
techniques (Abdulrahman
et al., 2021).
Tensorflow
The
most used deep learning and machine learning library currently in use is this
one. It quickly gained popularity and surpassed competing libraries due to the
ease of use of the API.
SimpleCV
A
system for creating computer
vision applications is
called SimpleCV. It provides access to several computer vision technologies on
any OpenCV, pygame, and other platforms. You need this program if all you need
to do is finish the task and you don’t want to learn all the specifics of image
processing. SimpleCV is the best option if rapid prototyping is required.
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