Automatic Identification of Pollen in Microscopic Images

• Type: Article in International Conference Proceedings Book
• Date: 2018

Authors

Santos, EMDS (Author) Other; marcal, ars (Author) FCUP

Conference proceedings International

Title: European Congress on Computational Methods in Applied Sciences and Engineering: ECCOMAS 2017: VipIMAGE 2017

Pages: 535-543

6th ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing (VipIMAGE)

Porto, PORTUGAL, OCT 18-20, 2017

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Other information

Authenticus ID: P-00N-5VT

DOI: 10.1007/978-3-319-68195-5_58

Abstract (EN): A system for the identification of pollen grains in bright-field microscopic images is presented in this work. The system is based on segmentation of raw images and binary classification for 3 types of pollen grain. The segmentation method developed tackles a major difficulty of the problem: the existence of clustered pollen grains in the initial binary images. Two different SVM classification kernels are compared to identify the 3 pollen types. The method presented in this paper is able to provide a good estimate of the number of pollen grains of Olea Europea (relative error of 1.3%) in microscopic images. For the two others pollen types tested (Corylus and Quercus), the results were not as good (relative errors of 14.5% and 20.3%, respectively).

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 9