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Preprocessing dan Features Extraction

Preprocessing dan Features Extraction. Pengertian. Preprocessing adalah proses pengolahan data asli sebelum data tsb diolah dgn JST. Tujuan preprocessing , diantaranya : Menghilangkan noise Memperjelas features (fitur) data Memperkecil / memperbesar ukuran data

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Preprocessing dan Features Extraction

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  1. PreprocessingdanFeatures Extraction

  2. Pengertian • Preprocessing adalah proses pengolahan data asli sebelum data tsb diolah dgn JST. • Tujuan preprocessing, diantaranya: • Menghilangkan noise • Memperjelas features (fitur) data • Memperkecil / memperbesar ukuran data • Mengkonversi data asli agar diperoleh data yg sesuai kebutuhan

  3. Contoh preprocessing • Mengubah citra RGB  gray-scale • Binerisasi citra • Croping citra • Resize citra • Edge detection / edge enhancement • Thinning

  4. Keuntungan preprocessing • Data lebih siap diolah dgn JST • Data sesuai dengan kebutuhan JST, misalnya pada proses binerisasi dan bipolarisasi • Fitur data lebih jelas

  5. Kerugian preprossesing • Perlu tambahan waktu komputasi, shg pengolahan data secara keseluruhan lebih lama • Algoritma preprocessing kadang-kadang menghilangkan informasi penting

  6. Features Extraction • Features extraction adalah proses pengambilan ciri-ciri yg unik dari data yg akan diolah. • Tujuan feature extraction diantaranya: • Memperkecil jumlah data • Mengambil informasi yg terpenting dari data yg diolah • Mempertinggi presisi pengolahan

  7. Contoh features extraction • Edge detection / edge enhancement • Separasi / pemisahan warna • Pencarian nilai-nilai ekstrim (tertinggi atau terendah) • Penghitungan banyaknya sudut

  8. Contoh enhancement

  9. Contoh Thinning

  10. Contoh Feature Extraction Gambar asli Gambar gray-scale

  11. Contoh Feature Extraction 00100 01100 00100 00100 00100 00100 00100 01110 Gambar biner

  12. Catatan • Preprocessing harus disesuaikan dgn kebutuhan data • Features extraction memerlukan kreatifitas dan kecermatan peneliti • Obyek yg sama dapat diambil fitur-fitur yg berbeda

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