Ruri Suko Basuki, Ruri Suko
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QUALITY IMPROVEMENT OF OBJECT EXTRACTION FOR KEYFRAME DEVELOPMENT BASED ON CLOSED-FORM SOLUTION USING FUZZY CMEANS AND DCT-2D Basuki, Ruri Suko; Hariadi, Mochamad; Purnomo, Mauridhi Hery
Kursor Vol 7, No 2 (2013)
Publisher : University of Trunojoyo Madura

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Abstract

QUALITY IMPROVEMENT OF OBJECT EXTRACTION FOR KEYFRAME DEVELOPMENT BASED ON CLOSED-FORM SOLUTION USING FUZZY CMEANS AND DCT-2D aRuri Suko Basuki, bMochamad Hariadi, cMauridhi Hery Purnomo a,b,cFaculty of Industrial Technology, Dept. of Electrical Engineering Institut Teknologi Sepuluh Nopember, Kampus ITS Keputih, Sukolilo, Surabaya, Jawa Timur, Indonesia a Faculty of Computer Science, Dian Nuswantoro University Jalan Imam Bonjol, Semarang, Indonesia E-mail: a rurisb@research.dinus.ac.id Abstrak Penelitian ini bertujuan untuk meningkatkan kualitas ekstraksi obyek pada citra tunggal hasil pemecahan frame dari video sekuensial yang terkompresi. Kualitas hasil ekstraksi obyek dengan algoritma closed-form solution menurun karena adanya beberapa perubahan nilai intensitas pada channel RGB. Sehingga di sekitar batas tepi obyek hasil ekstraksi terlihat kasar baik secara visual maupun hasil pengukuran dengan Mean Squared Error (MSE) antara obyek hasil ekstraksi dengan ground truth. Untuk meningkatkan kualitas hasil ekstraksi objek, nilai threshold pada unknown region ditentukan melalui adaptive threshold yang diperoleh dengan mengaplikasikan algoritma Fuzzy C-Means (FCM). Pemilihan algoritma FCM karena dalam penelitian sebelumnya algoritma ini menunjukkan hasil yang lebih robust dibandingkan algoritma Otsu untuk mendapatkan nilai threshold yang optimal. Sedangkan untuk menghaluskan obyek di sekitar daerah batas tepi digunakan filter Discrete Cosine Transform (DCT) – 2D. Dari 10 obyek yang digunakan dan dievaluasi dengan MSE menunjukkan peningkatan rata-rata sebesar 31.55%. Namun pendekatan ini tidak begitu robust pada citra yang memiliki kemiripan warna. Penggabungan pendekatan ini dengan optimasi cost function dalam alpha region pada basis spectrum diharapkan mampu meningkatkan kinerja algoritma ekstraksi obyek pada penelitian selanjutnya. Kata kunci: Closed-form Solution, Algoritma Fuzzy C-Means, Discrete Cosine Transform-2D. Abstract The research is aimed to improve the quality of the extraction of the object in a single image resulted from frame’s fragmentation of sequential compressed video. The quality of the extracted objects with closed-form solution algorithm decreased due to some changes in the intensity values on the RGB channel. Thus, the extraction result around the boundary edges of objects visually seemed to be rough and when it was measured with the Mean Squared Error (MSE) beween the object extraction results with ground truth. To improve the quality of the extracted object, the threshold value on unknown region was determined by adaptive threshold obtained by applying the Fuzzy C-Means algorithm (FCM). FCM algorithm is chosen since in the previous research this algorithm gives more robust results than Otsu algorithm to obtain the optimal threshold value. Meanwhile, to eliminate noise around the border area, this research applies Discrete Cosine Transform (DCT) - 2D filters. The result of 10 objects used and evaluated with the MSE showed an average increase of 31.55%. However, this approach is not so robust to images having similar color. Combination of this approach with optimization of the cost function on the alpha region based on spectrum is expected improving the performance of object extraction algorithm for the next research. Key words: Closed-form Solution, Fuzzy C-Means Algorithm, Discrete Cosine Transform-2D