Researchers at Northumbria University, England, have developed a new method that uses artificial intelligence (AI) to improve visual search engines. The Deep Discoveries project creates a search platform that identifies and combines digitized images to facilitate the user experience.
Instead of typing a keyword into a conventional search box, the new visual search uses a primary query image and integrated computer vision to find similar collections based on pre-programmed criteria such as colors, texture patterns and geometric shapes.
“We found objective ways to visually demonstrate the artificial intelligence reasoning to improve search criteria within the platform. After several attempts, we were able to improve the visual search engine using much more complex image comparison functions”, explains design professor Jo Briggs, co-author of the study.
Want to catch up on the best tech news of the day? Go and subscribe to our new channel on youtube, Canaltech News.
Every day a summary of the main news in the tech world for you!
User experience
The new method of visual research was implemented in the collection of the British National Archives to catalog thousands of digitized collections. The idea is to create an interface capable of making search engines more precise, using specific parts of images to find similar items.
Every day a summary of the main news in the tech world for you!
The new method of visual research was implemented in the collection of the British National Archives to catalog thousands of digitized collections. The idea is to create an interface capable of making search engines more precise, using specific parts of images to find similar items.
Deep Discoveries is one of eight projects funded by the cultural program that aims to open the British National Archives collection to the world. The five-year initiative will benefit the public and researchers, making heritage collections more accessible to all users.
“The design process led us to reach a common understanding that allowed us to create a prototype in real time, accommodating the different points of view between the teams involved in this multidisciplinary project. With that, it was possible to develop a robust and easy-to-use platform”, adds the software engineer of the British National Archives Bernard Ogden.
The Deep Discoveries project uses new machine learning methods to create a computer vision search platform that can identify and match images in scaled digitized collections . The search technology focuses on specific themes, for example, it can recognize a rose in a textile pattern and the same flower in an herbarium or in a ceramic vase.
Visual search identifies common patterns in different objects (Image: Reproduction/British National Archive)660
With this visual search system, researchers want to create a network of collections with specific images from across the UK, eliminating the need for a single type of unifying collection based on searching for keywords such as woodcuts, paintings, frescoes or photographs.
“Create an integrated and accessible digital collection requires research and implementation of many standards and new technologies. But the initiative also opens the door to new playful and creative methods of search and discovery, such as computer vision research, which can lead to unexpected ways of public involvement with digitized images”, concludes the head of research at the British National Archive Lora Angelova.
Source: Northumbria University
Did you like this article?
Subscribe your email on Canaltech to receive daily updates with the latest news from the world of technology.
source