Application of Artificial Intelligence in Image Processing
The movement of artificial intelligence has taken the global industries by storm. The application of AI in image processing is one of the prominent concepts followed in the industries worldwide.
The contemporary AI technique will enable in executing the face recognition functionalities. It will also help in detecting and recognizing the objects/ state of actions that are enclosed within an image or video.
The concept of image processing and computer vision are the two crucial elements that are required for developing a fully-scaled AI model. Nearly 75-80% of the AI models are built on these two significant aspects.
Before we take a deeper look into the subject matter, here’s a brief on ‘image processing’.
Image processing is the procedure of manipulating an image for two prime purposes – enhancing the image quality or extracting the vital details from an image. Most of the organizations tend to follow two foremost kinds of image processing – analog image processing, wherein, the concept is used to process a hard copy of images. The second one being digital image processing, wherein, the digital images are manipulated with the support of computer algorithms.
Image processing is broadly incorporated for the following objectives:
Processing the images to be presented in a meaningful way through the visualization
Enhancing the image quality of processed images
Easing the process of image retrieval
Helping you to measure the objects in an image through object recognition
Enabling object distinguishing and classification in an image
In simple terms, the image processing technique is all about extracting the specific features of an object. The application of the artificial intelligence model in image processing is widely used for image detection and image classification.
The concept of image classification is widely categorized into two sub-domains – classifiers and detectors.
Need for Artificial Intelligence on Image Processing
Processing of colored images
But, most of the business organizations face the difficulty to efficiently process the bulk of images or data every day. And to overcome such challenges, implementing the concept of machine learning algorithms can turn out to be productive. The techniques of machine learning and deep learning will speed up the process of image processing.
Artificial intelligence will support your business to deal with the different image processing activities such as image classification and detection. The artificial intelligence companies ensure to incorporate authentic and reliable tools and software for simplifying your business operations.
The most commonly used open-source library for the AI-centered image processing service is the OpenCV. The library comprises countless machine learning algorithms and it comes with programming languages such as Java, Python, C++, supporting the desktop and mobile OS.
The OpenCV library comes up with various components namely object detection element, an image processing element, and machine learning model.
Next, a widely-used open-source library is the Aforge.Net, developed for the .NET framework.
When talking about the AI framework used in image processing, the most frequently used one is ‘TensorFlow and Keras. These are the one of renowned open-source frameworks that supports both the deep learning and machine learning models. It has a wide prominence in dealing with the image processing projects.
A majority of the ML models that are used for image processing utilize the concept of deep learning and neural networks. With the assistance of these aspects, the machines can be trained to interpret the images in a specified way as required by an image processing project.
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