Ekstraksi Fitur Berdasarkan Deskriptor Bentuk dan Titik Salien Untuk Klasifikasi Citra Ikan Tuna

Ratri Enggar Pawening, Agus Zainal Arifin, Anny Yuniarti


Abstract. The manual classification of fish causes problems on accuracy and execution time. In the image of tuna, beside the shape feature, local features is also necessary to differentiate the types of fish especially which have a similar shape. The purpose of this study is to develop a new feature extraction system which integrates point of saline and the shape of descriptor to classify the image of tuna. The input image is then transformed into HSV format. Hue channel is selected for the segmentation process. Shape descriptors are extracted by using Fourier Descriptor (FD) and the saline points are extracted using Speeded Up Robust Features (SURF). The results of local features are performed by Bag of Feature (BOF). Feature integration combines shape descriptor and saline features with appropriate weight. Experimental results show that by integrating features, the classification problems of fish with similar shape can be resolved with an accuracy of classification acquired by 83.33%.

Keywords: feature extraction, fourier descriptor, surf, classification, tuna fish image

Abstrak. Klasifikasi secara manual yang dilakukan berdasarkan bentuk, tekstur, dan bagian tubuh ikan dapat menimbulkan permasalahan pada akurasi dan waktu klasifikasi. Pada citra ikan tuna, selain diperlukan fitur bentuk juga diperlukan fitur lokal untuk membedakan jenis ikan terutama yang memiliki bentuk secara visual mirip. Tujuan penelitian ini adalah mengembangkan sistem ekstraksi fitur baru yang mengintegrasikan deskriptor bentuk dan titik salien untuk klasifikasi citra ikan tuna. Segmentasi diawali dengan mengambil kanal Hue pada citra HSV. Deskriptor bentuk diekstrak menggunakan Fourier Descriptor dan titik salien diekstrak menggunakan Speeded Up Robust Features. Untuk menyamakan dimensi dilakukan pemrosesan menggunakan Bag of Feature. Kedua jenis fitur yang sudah diperoleh dilakukan integrasi dengan mempertimbangkan bobot masing-masing fitur. Uji coba dilakukan pada dataset tiga jenis ikan tuna dengan 10-fold cross validation. Hasil uji coba menunjukkan dengan mengintegrasikan deskriptor bentuk dan titik salien permasalahan klasifikasi ikan tuna dengan bentuk yang mirip dapat diselesaikan dengan akurasi klasifikasi sebesar 83,33%.

Kata Kunci: ekstraksi fitur, deskriptor fourier, surf, klasifikasi, citra ikan tuna

Full Text:



. Aakif, A., & Khan, M. F. 2015. Automatic classification of plants based on their leaves. Biosystems Engineering, 139, 66-75.

. Bay, H., Ess, A., Tuytelaars, T., & Gool, L. V. 2008. Speeded-Up Robust Features (SURF). Computer vision and image understanding, 110(3), 346-359.

. Chen, Z., & Sun, S. K. 2010. A Zernike moment phase-based descriptor for local image representation and matching. IEEE Transactions on Image Processing, 19(1), 205-219.

. El-gayar, M. M., & Soliman, H. 2013. A comparative study of image low level feature extraction algorithms. Egyptian Informatics Journal, 14(2), 175-181.

. Hu, M. K. 1962. Visual pattern recognition by moment invariants. Information Theory, IRE Transactions on, 8(2), 179-187.

. Hu, Y., & Li, Z. 2013. An improved shape signature for shape representation and image retrieval. Journal of Software, 8(11), 2925-2929.

. Kadir, A. 2015. Leaf Identification Using Fourier Descriptors and Other Shape Feature. Gate to Computer Vision and Pattern Recognition, 1, 3-7.

. Li, K., Wang, F., & Zhang, L. 2015. A New Algorithm for Image Recognition and Classification Based on Improved Bag of Features Algorithm. Optik-International Journal for Light and Electron Optics, 1-9.

. Nabizadeh, N., & Kubat, M. 2015. Brain tumors detection and segmentation in MR images: Gabor wavelet vs statistical features. Computer and Electrical Engineering, 1-16.

. Yang, H. Y., Li, Y. W., Li, W. Y., Wang, X. Y., & Yang, F. Y. 2014. Content-based image retrieval using local visual attention feature. Journal of Visual Communication and Image Representation, 25(6), 1308-1323.

DOI: https://doi.org/10.24002/jbi.v7i3.660


  • There are currently no refbacks.