Title
Milk purity recognition software through image processing
Date Issued
01 January 2019
Access level
open access
Resource Type
journal article
Publisher(s)
Science and Information Organization
Abstract
Currently in Peru, there is a per capita milk consumption of 87 kg per year; however, the Food and Agriculture Organization of the United Nations (FAO) recommends a consumption of 120 kg per person; the industry, when the milk is acquired from small livestock suppliers, does not analyze the milk before buying it, which there is a high risk that the milk is adulterated with water, in this sense, it proposes an alternative way of preliminary detection of the presence of water in milk, only through a laser a photograph, which greatly reduces the costs of milk analysis. Milk contains different nutrients, vitamins and minerals, which are beneficial for people, so it is very known if it is adulterated or not, that way to prevent diseases. In this document, the reader will read an alternative to the existing methods for the analysis of milk, for the presented method the application of Matlab Classification Learner and the fine K-Nearest Neighbors (KNN) algorithm were used, in which a success rate of 95.4% was obtained.
Start page
452
End page
455
Volume
10
Issue
11
Language
English
OCDE Knowledge area
Sistemas de automatización, Sistemas de control Ciencia animal, Ciencia de productos lácteos
Scopus EID
2-s2.0-85077233444
Source
International Journal of Advanced Computer Science and Applications
ISSN of the container
2158107X
Sources of information: Directorio de Producción Científica Scopus