Skip to content
naulon
Not checkedNot checked for notices yet.

A dataset for automatic contrast enhancement of microscopic malaria infected blood RGB images

J. Somasekar, G. Ramesh, Gandikota Ramu and 3 more

Data in Brief · 2019

doi:10.1016/j.dib.2019.104643 (opens in a new tab)

We email you when a new notice or a question about this paper appears.

Abstract

In this article we introduce a malaria infected microscopic images dataset for contrast enhancement which assist for malaria diagnosis more accurately. The dataset contains around two hundred malaria infected, normal, species and various stages of microscopic blood images. We propose and experimentally demonstrate a contrast enhancement technique for this dataset. This simple technique increases the contrast of an image and hence, reveals significant information about malaria infected cells. Experiments on the dataset show the superior performance of our proposed method for contrast enhancement of malaria microscopic imaging. Keywords: Malaria diagnosis, Low contrast images, Histogram equalization, Microscopic RGB blood images, Contrast enhancement

Abstract licence: CC BY-NC

Reads

Read by people on this page

None yet.

Checked or read by AI through naulon

None yet.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

Are you an author?

Is this your paper?

Claim it to add your note and be paid when agents cite it. Free.