AI Changing the Dynamics of Image Processing Technology

Artificial intelligence, or AI, is making waves across industries, catapulting technological advancements to prodigious heights. Because of its myriad advantages, AI's application in image processing is also picking up steam, globally. From medical diagnostics and facial recognition to pattern recognition, AI-driven image processing, assisted by Machine Learning and computer vision, has come a long way, breaking fresh ground.

Before we delve into the crucial role AI plays in image processing, let's first understand what image processing exactly is.

Image processing involves the process of transforming an image into a digital format. The digitally enhanced image then undergoes different operations to generate valuable data/information. Image processing involves various techniques to identify and classify objects within an image. Its primary function is to improve the overall quality of the processed images and effectively present them in different formats, such as photo negatives, X-rays, enhanced images, and more. Image processing techniques also simplify the procedure of storing and retrieving images, besides facilitating the differentiation and categorization of the objects.

However, manually processing images or data in bulk can be a daunting task for businesses. With advancements in AI technology, the traditional methods of image processing are taking a backseat as forward-thinking businesses are increasingly implementing AI techniques to accelerate and streamline image processing procedures. AI leverages image processing algorithms via machine learning and deep learning techniques to expedite the stages of image processing.

Application Areas of AI in Image Processing

With the advancements in image processing technologies, AI is being widely used for simplifying business operations. This groundbreaking technology is gradually transforming how we analyse, interpret, and manipulate images. When utilised in the field of image processing, AI can facilitate prompt medical diagnosis, enhance face recognition, and bolster security functionalities in public spaces. It also facilitates the instant identification of intruders, objects, and patterns within live images or videos.

One of the most remarkable aspects of AI is its capacity to promptly identify, classify, augment, enhance, and reconstruct images. Moreover, AI can be effectively utilised for morphological image processing. Through its unique capabilities, AI can optimise and streamline various image processing techniques in the following ways:

● Image Recognition: AI-powered image processing systems leverage convolutional neural networks (CNN) to enhance object detection and classification for increased accuracy and speed. Deep learning algorithms and computer vision techniques enable AI-enabled image processors to identify objects, people, or scenes in real-time. This capability finds application in security systems, facial recognition, automated image categorisation, and content moderation. Likewise, Artificial intelligence can generate realistic images by manipulating, and fabricating visual content, employing techniques such as generative adversarial networks (GAN). This advancement has far-reaching implications in graphic design, entertainment, and virtual reality apps.

● Image Enhancement & Restoration: AI techniques have made significant strides in enhancing image quality. AI uses deep learning algorithms to generate visually appealing, high-resolution images from low-resolution inputs. The algorithms can also reduce noise, enhance details, adjust colours, and remove artefacts seamlessly. This plays a substantial role in medical imaging, where clear and precise images are indispensable for accurate diagnosis and treatment planning. Leveraging the capabilities of image intelligence in the field of medical diagnosis is poised to be a groundbreaking advancement with the potential to significantly expedite the diagnostic process. By providing healthcare professionals with access to superior visual data, this approach can significantly enhance patient outcomes.

● Automated Image Analysis: AI algorithms also facilitate automated image analysis. It can automatically identify and classify objects and patterns to extract useful data from images. Several domains have benefited from this breakthrough, including medical diagnostics, manufacturing quality control, surveillance systems, and autonomous vehicles. AI-driven image processing also facilitates real-time analysis and processing of images and videos. AI-powered algorithms are capable of processing visual data in milliseconds, enabling quick decision-making and automation.

● Image Segmentation and Object Detection: AI-driven image segmentation involves the partitioning of an image into multiple segments based on colour, texture, and other elements. AI helps identify and analyse the specific parts within an image, leading to more accurate and specific insights. In this procedure, every individual pixel within the image is assigned a distinct object category. It is utilised in medical image analysis, scene understanding, and object tracking. Image intelligence helps identify and analyse different components within an image, leading to more accurate and specific insights.

● Content-Based Image Retrieval: AI also empowers content-based image retrieval systems, enabling users to search for images based on visual similarity or specific attributes. Through the extraction of pertinent features and descriptors, machines can effectively index and retrieve images from extensive databases. This technology finds practical applications in various domains such as e-commerce, art collections, and image-driven research, enabling users to swiftly and precisely locate pertinent images.

● Image Understanding and Interpretation: AI enables machines to understand the context and meaning behind visual data. By carefully analysing the content, connections, and contextual elements present in images, machines can gain a deep understanding of complex scenes, interpret visual information, and make well-informed decisions. This capability holds immense potential in domains such as autonomous systems, robotics, and augmented reality.

AI-powered open-source platforms like OpenCV, TensorFlow, Keras, etc., enable developers to access extensive machine learning algorithms in different programming languages. This enables greater accessibility to AI-driven image processing across platforms. Utilising deep learning and neural networks, these frameworks enable machines to interpret images precisely, enhancing the accuracy of image processing algorithms.

Wrapping Up!

Artificial intelligence is steadily revolutionising the process of analysing, interpreting, and manipulating images. As AI technology continues to evolve, it will continue to spearhead remarkable advances in image processing, ultimately paving the way for a future driven by enhanced visual intelligence. From assisting in medical diagnoses to optimising industrial processes, AI’s impact on image processing is far-reaching and holds immense promise for diverse industries.

Author: L.Centhilnathan Senior Vice President & Head of Division - Photo Imaging, FUJIFILM India