Metode Convex Hull dan Convexity Defects untuk Pengenalan Isyarat Tangan

Authors

  • Nina Yuliana Institut Teknologi Harapan Bangsa
  • Ken Ratri Retno Wardani Institut Teknologi Harapan Bangsa

DOI:

https://doi.org/10.61769/telematika.v11i2.139

Keywords:

IMK, Pengenalan Isyarat Tangan, Convex Hull, Convexity Defects, Freeman Chain Code, dan Maximum Inscribed Circle

Abstract

Teknik Interaksi Manusia dan Komputer (IMK) mengalami perkembangan pesat. Dibuktikan dengan banyak teknik baru dengan antarmuka yang alami dan mudah digunakan tanpa peralatan eksternal yang khusus. Pada penelitian ini diterapkan pengenalan isyarat tangan pada IMK agar dapat berinteraksi dengan komputer tanpa dibatasi oleh penggunaan tetikus. Isyarat tangan yang akan dikenali terdiri atas 8 isyarat yang merupakan kombinasi dari ibu jari, jari telunjuk, dan jari kelingking karena mewakili operasi dasar yang sering digunakan pada tetikus. Setiap jari dalam posisi direntangkan dan tidak berhimpitan. Tangan yang digunakan pada penelitian ini adalah tangan kiri. Background model dan sampel warna kulit diperlukan sebagai masukan. Pengolahan citra digunakan untuk mendapatkan segmentasi tangan dengan menggunakan algoritma Freeman Chain Code. Hasilnya digunakan pada proses ekstraksi fitur. Proses ekstraksi fitur terdiri atas algoritma: Convex Hull untuk mencari titik Hull sebagai ujung jari, Convexity Defects mencari titik defects sebagai deskripsi jari, dan Maximum Inscribed Circle (MIC) untuk deteksi titik pusat telapak tangan. Hasil penelitian berhasil mengenali isyarat tangan dengan nilai akurasi lebih dari 90% dengan kondisi pencahayaan kurang dan cukup.

 

Techniques of Human-Computer Interaction (HCI) growing rapidly. Many new techniques with a natural interface and easy to use without any special external equipment. In this research apply to the HCI hand gesture recognition to interact with  the computer without being limited by mouse. Hand gesture to be recognized consists of 8 cues, the combination of the thumb, forefinger and little finger to represent the basic operations of a mouse. Each finger in a stretched position, do not coincide, and the hands are used in this study are left hand. Background models and samples of skin color is required as input. Image processing is used to obtain the hand segmentation using Freeman chain code algorithms and the results will be used in the process of feature extraction.  The feature extraction process consists of  algorithms Convex hull to find points as fingertips, convexity defects  lookout point defects as a description of the fingers, and palms central point detection using maximum Inscribed circle (MIC). The results showed that the method of Convex Hull and Convexity Defects managed to recognize hand signals with an accuracy value of more than 90% with sufficient and less lighting conditions.

Author Biographies

Nina Yuliana, Institut Teknologi Harapan Bangsa

Nina Yulian, mahasiswi jurusan Teknik Informatika Institut Teknologi Harapan Bangsa  Bandung lulus tahun 2015.

Ken Ratri Retno Wardani, Institut Teknologi Harapan Bangsa

Ken Ratri Retno Wardani, menerima gelar Sarjana Teknik Informatika dari Sekolah Tinggi Sains dan Teknologi  pada tahun 1993. Menyelesaikan studi Magister di Institut Teknologi Bandung jurusan Teknologi Informasi dan aktif sebagai pengajar di Departement Teknik Informatika, Institut Teknologi Harapan Bangsa di Bandung. Bidang penelitian adalah pengolahan citra dan interaksi manusia komputer.

References

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Ankit Chaudhary, Jagdish L. Raheja, Shekhar Raheja. A Vision based Geometrical Method to find Fingers Positions in Real Time Hand Gesture Recognition, 2012.

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Cover Vol 11(2)

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Published

2017-02-22

Issue

Vol. 11 No. 2 (2016)

Section

Articles

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