"Digital intelligence will change all industries, so you better not lag behind." Dave Waters Image Processing in intelligent systems is a multi-year project that many people have worked on since the advent of artificial intelligence (AI).
Image processing In its infancy, it required a large number of manual inputs to provide computer instructions for accessing the output. These machines, known as Expert Systems, were trained to detect images.
According to the Gartner Institute for Technology Research, the number of industries that have used artificial intelligence over the past four years 270% increase.
We need a machine that can do more than just detect images. Advances in artificial intelligence have helped engineers design software that enhances human capacity to accurately view, understand, recognize and accurately describe photo and video content.
What is image processing?
In general, the set of processes that are performed on an image to obtain specific information and output from the same image is called image processing. There are two methods for image processing.
Analog image processing: This method is used to process printed
and printed images.
Digital image processing: Image processing in this method using algorithms Images are complicated and manipulated.
What is the main purpose of image processing?
With the help of image processing can be done Visually process the processed information. Like shaping invisible objects. Image processing can be used to improve the quality of the processed image, sharpen the image and restore the images. Image processing helps to measure objects inside the image. Image processing facilitates the classification of objects in the image, recognizes their position, and provides an overall understanding of the image by recognizing patterns.
How many steps does image processing take?
There are 8 steps to image processing, which we will explain step by step.
1. Image acquisition
Take a photo with a sensor and turn it into a controllable file.
2. Increase image quality (Image enhencement)
You can increase the quality of the input image and extract hidden details.
3. Image restoration
Any possible errors such as image blur, noise, or camera out of focus are removed to get a better view of the possible model and the basis of the mathematical model.
4. Color image processing
Color images and various color spaces are processed pseudocolor or RGB.
5. Image compression
This allows you to change the size and resolution of the image depending on your needs.
6. Morphological processing
In this step, the structure and shape of the object in the image are defined.
7. Image recognition
The unique properties of a particular object are detected using techniques such as object detection.
8. Representation and description
This step about visualization and information Manufactured.
Managing large amounts of image data manually is not an easy task. This is where AI and Machine Learning algorithms come into play. The use of artificial intelligence and machine learning increases the speed of information processing and produces quality output. Of course, to get quality results, you need to choose the right tools and methods. And lack of camera focus. That is why they need initial processing. There are two identification methods for digital image processing as well as initial processing:
This method is used to modify and improve the input image. With the help of various filters available, some features in the image can be removed or emphasized. Image noise can also be reduced.
2. Edge detection
This method is used to extract data and segment images in order to find object edges in processed images.
There are special libraries and frameworks You can use them to help with image processing.
Open source libraries for image processing Basics of Artificial Intelligence
Computer vision libraries include general image processing functions and algorithms. Several open-source libraries are available to help you develop computer image and vision processing capabilities.
Open Source Computer Vision Library or OpenCV
This library is a collection of libraries for computer vision and implements a number of popular algorithms in this field and related functions.
LTP-Library Lib makes it easy to share and maintain real-time applications by providing fast algorithms. This library provides a wide range of capabilities that can be used to solve mathematical problems and provides a set of classification tools and image processing algorithms and vision algorithms.
Using the intelligence algorithm Artificially, machines can interpret photos based on a specific need. In each industry, there are unique opportunities to perform image processing based on artificial intelligence. It's entirely up to you how you want to get the most out of it.