AI and image search: A duo for the future

How companies benefit from smart search technology

“Searching the complex data landscapes in companies offers a wide range of applications for artificial intelligence,” explains Christoph Wendl, expert for enterprise search solutions and CEO of Iphos IT Solutions. “AI helps companies efficiently analyze indexed files and help extract relevant information quickly. In addition to processing texts, we use machine learning to evaluate visual data. A good enterprise search system recognizes objects such as people, vehicles or technical devices in images and makes them easy to find using search terms. Users benefit from more intuitive handling and easier access to image files. “Artificial intelligence is a valuable addition to the company’s internal search. The reasons for this lie in the special features of the enterprise search software.”

Central, secure access to all company systems

Graphics, technical drawings, photos and even Photoshop files – different file formats and security levels often mean that image files are distributed across different systems and storage locations within the company. This fragmentation makes it difficult to search consistently and efficiently. Software such as enterprise search solutions can build a bridge between all data sources: “An efficient image search must fulfill the function of indexing and organizing files from all relevant storage locations,” explains Wendl. “This comprehensive data pool is fundamental in order to be able to meaningfully apply AI functionalities to all internal company data. Compliance with data protection aspects is integrated into the enterprise search software: by integrating existing authorization systems, users can only see what they are allowed to see.”

Semantic search for objects in images

The biggest drawback of manual image searches are the file names. If a considerable amount of work has not been done manually, you will be confronted with an abundance of images with cryptic letter-number combinations that say nothing about the content of the image. Searching these image archives becomes a lengthy and tedious process.
Implementing a semantic image search can help here. This attempts to interpret and index images based on meanings and concepts, rather than just relying on filenames or keywords manually assigned to the images.

“A good internal company search can be expanded using object recognition and context recognition technologies,” reports Wendl of the AI-supported solution approach. “Themes, concepts and objects are recognized in the images and indexed as potential search terms. This significantly improves the accuracy and relevance of results and makes the search experience largely intuitive. For example, if users need an advertising graphic that shows a computer, they just have to enter the term “PC” and select the right one from all the computer images recognized.” Employees are no longer dependent on metadata and meticulous naming standards alone when searching. Rather, all available image material can be searched precisely for the desired image content.

As a rule, good enterprise search solutions should also include synonym recognition. This means that PCs identified in images can be found even if the user does not search for “PC”, but rather for synonymous terms such as “computer”, “work station”, or “laptop”. Such combinations of technologies in search enormously increase the benefits of enterprise search in image search.

Automatic categorization thanks to artificial intelligence

“The tedious clicking through file paths that lead into deep folder structures is a thing of the past thanks to enterprise search technologies. File keywords can be assigned automatically using our AI's text recognition and object recognition algorithms. Images are automatically classified, which in turn promotes organized data management and increases productivity when dealing with image files.

User-friendly gallery view with thumbnails

The same applies when searching for files: image before text. The brain processes visual information many times faster than mere text. A pictorial representation of files forms the basis for an intuitive search experience. “After the automatic ranking according to relevance, one of our most important functions in the image search is the gallery view with thumbnails,” explains Wendl. “Special parsers and optical character recognition allow us to offer a reduced preview of image files directly in the results display. This also includes formats that cannot be displayed visually in Windows Explorer, such as Photoshop files.” New technologies are linked here with user-oriented representation, which allows for more efficient use of visual resources.

Character recognition to increase efficiency in the company

Enterprise Search has always relied on the integration of new technologies to make internal company searches more intelligent and intuitive. Another good example of successful use of technology in internal search engines is Optical Character Recognition (OCR). OCR allows machine-readable text to be recognized in the pixel information of images, graphics and scans - as is the case with scans of invoices, contracts or archived writings is. This is often the only way such documents can be found. It is therefore recommended for medium-sized and larger companies to integrate OCR functionality into the corporate search. “The intelligent combination of object recognition in the image and OCR text recognition can lead to synergies for a company,” says Christoph Wendl. “For example, it is possible to read the license plates of recognized cars in images using OCR, or to recognize brand names in product images.”