期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2017
卷号：8
期号：8
DOI：10.14569/IJACSA.2017.080809
出版社：Science and Information Society (SAI)
摘要：Shadow identification is important for food images. Different applications require an accurate shadow identification or removal. A shadow varies from one image to another based on different factors such as lighting, colors, shape of objects, and their arrangement. This makes shadow identification complex problem and lacking systematic approach. Machine learning has high potential to be used for shadow recognition if it is used to train algorithms on wide number of scenarios. In this article, Extreme Learning Machine (ELM) has been used to identify shadow in shadow mask area. This shadow mask area was determined in the image based on edge detection, and morphological operations. ELM has been compared with Support Vector Machine (SVM) for shadow identification and shown better performance.
关键词：Extreme machine learning; shadow identification; food images; support vector machine; edge detection; color spaces
