A dynamic, real-time algorithm for seed counting

Mitchell L. Neilsen, Chaney Courtney, Siddharth Amaravadi, Zhiqiang Xiong, Jesse Poland, Trevor Rife

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


Kansas State University is a world leader in the study of wheat genetics to develop new varieties that can tolerate a wide range of environmental conditions. Field Book, a new mobile application, was developed to modernize plant breeding programs around the world. Building off its success, we've developed several additional mobile apps for plant breeding. As a part of this effort, novel image analysis algorithms are being developed to model and extract plant phenotypes. This paper describes a dynamic, real-time algorithm to accurately count seeds using a modest mobile device. There are many directions for future research to enhance the algorithm's performance and accuracy. The new algorithm can be used to count a wide variety of different types of crop seeds for high-throughput phenotyping.
Original languageEnglish (US)
Title of host publication26th International Conference on Software Engineering and Data Engineering, SEDE 2017
PublisherThe International Society for Computers and Their Applications (ISCA)isca@ipass.net
Number of pages6
ISBN (Print)9781943436095
StatePublished - Jan 1 2017
Externally publishedYes


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