Special Issue on Computer Vision For Food Quality

Journal of Food Quality (CFP) Computer vision is powerful technology that has recently increased for the automatic inspection of food. Typical target applications include sorting, quality estimation from external or internal properties, process monitoring, and evaluation of experimental treatments. The capabilities of computer vision technology exceed the limited human capacity to evaluate long-term processes objectively or to appreciate events that take place outside the visible electromagnetic spectrum and the success strongly depends on a number of factors: sensor type, lighting, type of product, required processing speed, segmentation, recognition and classification strategies, and availability of training data, and so on. We invite researches to contribute original articles as well as review articles that address a wide range of theoretical and practical issues. Potential topics include but are not limited to the following:

Authors can submit their manuscripts through the Manuscript Tracking System at http://mts.hindawi.com/submit/journals/jfq/cvfq/. Manuscript Due Friday, 30 June 2017 First Round of Reviews Friday, 22 September 2017 Publication Date Friday, 17 November 2017

Lead Guest Editor Paolo Napoletano, University of Milano-Bicocca, Milan, Italy Guest Editors Raimondo Schettini, University of Milano-Bicocca, Milan, Italy Jose Blasco-Ivars, Instituto Valenciano de Investigaciones Agrarias (IVIA), Valencia, Spain Mohd Z. Abdullah, Universiti Sains Malaysia, Penang, Malaysia Won Suk Lee, University of Florida, Gainesville, USA.

About this Journal Journal of Food Quality is a peer-reviewed, Open Access journal that publishes original research articles as well as review articles related to all aspects of food quality. The most recent Impact Factor for Journal of Food Quality is 0.755 according to the 2015 Journal Citation Reports released by Thomson Reuters in 2016. Content published prior to 2017 is hosted on the Wiley Online Library. Journal of Food Quality currently has an acceptance rate of 21%.