Publiora

Menghubungkan ke Publiora...

Publiora

Herb Leaves Recognition using Gray Level Co-occurrence Matrix and Five Distance-based Similarity Measures

Isnanto, R. RizalRiyadi, Munawar AgusAwaj, Muhammad Fahmi
International Journal of Electrical and Computer Engineering (IJECE) (Sinta 1)Vol. 0 No. 01 Juni 2018
DOI10.11591/ijece.v8i3.pp1920-1932

Abstrak

Herb medicinal products derived from plants have long been considered as an alternative option for treating various diseases.  In this paper, the feature extraction method used is Gray Level Co-occurrence Matrix (GLCM), while for its recognition using the metric calculations of Chebyshev, Cityblock, Minkowski, Canberra, and Euclidean distances. The method of determining the GLCM Analysis based on the texture analysis resulting from the extraction of this feature is Angular Second Moment, Contrast, Inverse Different Moment, Entropy as well as its Correlation.  The recognition system used 10 leaf test images with GLCM method and Canberra distance resulted in the highest accuracy of 92.00%. While the use of 20 and 30 test data resulted in a recognition rate of 50.67% and 60.00%.

Kata Kunci

canberra distancechebyshev distancecity-block distanceeuclidean distancegray-level cooccurrence matrixminkowski distance

Cari jurnal yang tepat untuk naskah Anda

MatchMind AI mencocokkan abstrak naskah Anda dengan ribuan jurnal terakreditasi dan menampilkan rekomendasi terbaik beserta alasannya.

Coba MatchMind

Lihat profil lengkap jurnal ini

Waktu review, biaya APC, statistik sitasi, indeksasi Scopus, dan banyak lagi.

Buka International Journal of Electrical and Computer Engineering (IJECE)

Artikel ini juga tersedia di situs resmi jurnal.

Herb Leaves Recognition using Gray Level Co-occurrence Matrix and Five Distance-based Similarity Measures | International Journal of Electrical and Computer Engineering (IJECE) | Publiora