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Mobile real time logo detection and recognition using ORB feature

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NTU MMAI 2014 final project
D03922016 楊存毅 D03922003 許洸睿

Logo is very common in every social media or real world product. If we can take a picture of the logo by our smartphone and retrieve the information of the logo on the internet, we can determine whether to buy the product or not. Since the contaminated food problem is become more and more serious in Taiwan, we want to build a mobile system to recognize these products and avoid to buy them.

We try to build a real time logo detection and recognition system. The feature we choose is ORB feature [1] which is fast and rotation invariant. We have online and offline process.
1. Offline: Collect our template logo dataset for the recognition system. We save the ORB features of each template logo set on the phone. We also collect the information of the logo from the internet, and define the rate of unscrupulousness (RU) for the logo.
2. Online: Take a picture by your phone from the real world. We extract the ORB feature from the picture you just take and match with each template logo set. After that, we adopt spatial verification step using SCSM [2] and remove the outlier correspondences. Not only we can know the best match template logo type, but also we can localize the location of the logo from the picture you take. If the logo is retrieved, the system will show the logo picture and RU for the logo.


[1] ORB: an efficient alternative to SIFT or SURF
[2] Object retrieval and localization with spatially-constrained similarity measure and k-NN re-ranking
[3] OpenCV学习笔记[5]FLANN特征匹配


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