Work

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

Year: 2025

Type: article

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.

Source: Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi)

DOI: 10.35870/jtik.v9i3.3826

Authors: Edhy Poerwandono, M. Endang Taufik

Institution: Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika

Language: English

Topic: Image Retrieval and Classification Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4409538327

FWCI:

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