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Visual Search Goes Open Source

FOR IMMEDIATE RELEASE
Contact: media@yesexactly.com
413-325-8251

Greenfield, MA — August 17, 2017 — Visual Search is now open source.

Zappen ® (https://www.zappen.co) and Yes Exactly, Inc. ® today announced a FOSS production-ready framework for mobile application development utilizing computer vision, image recognition, and augmented reality (AR) technologies. Previously, working implementations of visual search have only been available through proprietary APIs such as that offered by Google Lens (still in beta).

“Zappen is like a QR Code on steroids,” says Yes Exactly CEO Elizabeth Gadwa. “You can take a picture with your phone and immediately connect to websites, apps, and social media.”

Discogs, the biggest and most comprehensive music database and international marketplace, plans to integrate Zappen visual search technology into its popular music database and collection management app. “At the core of Discogs is our commitment to embrace and contribute to the open source community,” says Chad Dahlstrom, COO at Discogs. “Our work with Zappen puts that commitment in action by contributing to Zappen’s ability to improve image recognition with scalability testing. We’re excited to be a part of this continuing innovation with the Zappen team as we begin working to implement this technology into the Discogs App.”

Zappen combines a cross-platform React Native app with a PASTEC / ORB / OpenCV backend employing the “visual words” algorithm for image recognition and search.

“We were able to boost our image match success rate to over 95% by optimizing hardware settings and server-side processing filters,” says Zappen cofounder Erik Amlee. “Having a team with a strong technical graphics background was key.”

Server-side image recognition confers several benefits over QR, including enhanced security, brand recognition, and the ability to re-use existing collateral and signage.

Zappen returns 98.7% accurate results in 3- 5 seconds, under normal lighting and bandwidth conditions. It has been tested for accuracy with a dataset containing 100,000 images and is currently undergoing further scalability and performance testing. The technology is best suited for 2D images such as logos, posters, signs, and product packaging. Potential uses include public key verification, electronic currency transactions, signs, exhibits, and advertising.

The Zappen visual search repository is available on Github under the LGPL 3.0 license at https://github.com/ZappenVDNS. Future planned enhancements include machine learning and integration with the EmerDNS distributed domain name system.

Try adding your own images and links (no coding required) with our free demo.