Identification of Flower Type Images Using KNN Algorithm With HSV Color Extraction and GLCM Texture

Edhy Poerwandono; M. Endang Taufik

doi:10.62951/router.v3i1.385

Authors

Edhy Poerwandono STIKOM Cipta Karya Informatics
M. Endang Taufik STIKOM Cipta Karya Informatics

DOI:

https://doi.org/10.62951/router.v3i1.385

Keywords:

Identification, HSV, GLCM, K-Nearest Neighbor

Abstract

Due to the variety of types of flowers that exist and having and tracking each variety, making plant lovers and cultivators difficult to distinguish in determining the type of flower, it takes a very long time to find out the type of flower if you only rely on the five senses. With the application of the K-Nearest Neighbor algorithm and feature extraction of color and texture, it is very helpful in image processing to identify flowers more easily and shorten the time, with the greatest accuracy of 71% using the K-7 value, the flower was successfully carried out.

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