Volume 10, Number 3

A Novel Data Dictionary Learning for Leaf Recognition

  Authors

Shaimaa Ibrahem¹, Yasser M. Abd El-Latif² and Naglaa M. Reda², ¹Higher Institute for Computer Sciences and Information System, Egypt and ²Ain Shams University, Egypt

  Abstract

Automatic leaf recognition via image processing has been greatly important for a number of professionals, such as botanical taxonomic, environmental protectors, and foresters. Learn an over-complete leaf dictionary is an essential step for leaf image recognition. Big leaf images dimensions and training images number is facing of fast and complete data leaves dictionary. In this work an efficient approach applies to construct over-complete data leaves dictionary to set of big images diminutions based on sparse representation. In the proposed method a new cropped-contour method has used to crop the training image. The experiments are testing using correlation between the sparse representation and data dictionary and with focus on the computing time.

  Keywords

Leaf image recognition, Dictionary learning, Sparse representation, Online Dictionary Learning.