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Research Article | Open Access |

Shadow Identification in Food Images using Extreme Learning Machine

Author 1: SALWA KHALID ABDULATEEF Author 2: MASSUDI MAHMUDDIN Author 3: NOR HAZLYNA HARUN
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 8, No. 8 · Published 2017

DOI: 10.14569/IJACSA.2017.080809

Abstract

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.

Keywords

How to Cite this Article

ABDULATEEF, S. K., MAHMUDDIN, M., & HARUN, N. H. (2017). Shadow Identification in Food Images using Extreme Learning Machine. International Journal of Advanced Computer Science and Applications, 8(8). https://doi.org/10.14569/IJACSA.2017.080809

ABDULATEEF, SALWA KHALID, et al.. "Shadow Identification in Food Images using Extreme Learning Machine." International Journal of Advanced Computer Science and Applications, vol. 8, no. 8, 2017, https://doi.org/10.14569/IJACSA.2017.080809.

@article{ABDULATEEF2017,
  title     = {Shadow Identification in Food Images using Extreme Learning Machine},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {8},
  number    = {8},
  year      = {2017},
  publisher = {The Science and Information Organization},
  author    = {SALWA KHALID ABDULATEEF and MASSUDI MAHMUDDIN and NOR HAZLYNA HARUN},
  doi       = {10.14569/IJACSA.2017.080809},
  url       = {https://doi.org/10.14569/IJACSA.2017.080809}
}

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