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Fuzzy for Image Processing

fuzzy logic. Fuzzy for Image Processing. Penyusun: Tri Nurwati (Dari berbagai sumber). fuzzy logic. Fuzzy Image Processing .

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Fuzzy for Image Processing

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  1. fuzzy logic Fuzzy for Image Processing Penyusun: Tri Nurwati (Dari berbagai sumber)

  2. fuzzy logic Fuzzy Image Processing • Fuzzy image processing is the collection of all approaches that understand, represent and process the images, their segments and features as fuzzy sets. The representation and processing depend on the selected fuzzy technique and on the problem to be solved.(From: Tizhoosh, Fuzzy Image Processing, Springer, 1997)

  3. fuzzy logic Struktur pengolahan citra dengan fuzzy

  4. fuzzy logic Proses pembuatan fuzzy pada pengolahan citra Tidak seperti penggunakan logika fuzzy di suatu plant, untuk pengolahan citra pembuatan fuzzy melalui proses: • coding of image data (fuzzification) • the middle step (modification of membership values • decoding of the results (defuzzification)

  5. fuzzy logic Proses pembuatan fuzzy pada pengolahan citra • Setelah data citra ditransformasikan dari level gray ke dalam membership function (fuzzification), dalam proses ini dibutuhkan ketelitian dalam pengelompokan dan penentuan nilai membership input dan output

  6. fuzzy logic

  7. fuzzy logic Kelebihan pengolahan citra dengan menggunakan logika fuzzy • Teknik logika fuzzy sangat mumpuni dalam pemrosesan/pengolahan dan representatif pengetahuan (rule) • Teknik logika Fuzzy dapat mengatur keambiguan (mirip) dan hal-hal yang relatif

  8. fuzzy logic Kelebihan pengolahan citra dengan menggunakan logika fuzzy • Teori set fuzzy mempunyai kelebihan dapat mempresentasikan dan memproses pengetahuan pengguna dalam bentuk aturan “it-then”

  9. fuzzy logic

  10. fuzzy logic Contoh:colour = {yellow, orange, red, violet, blue}

  11. fuzzy logic Contoh:warna gray: gelap, gray, dan terang

  12. fuzzy logic Aplikasi : • Histogram-based gray-level fuzzification (or briefly histogram fuzzification)contoh: Perbaikan ketajaman warna image (seperti gambar panda di atas) • Local fuzzification (contoh: deteksi tepi) • Feature fuzzification (Scene analysis, object recognition)

  13. fuzzy logic Perbaikan Image dengan Fuzzy • many researchers have applied the fuzzy set theory to develop new techniques for contrast improvement

  14. fuzzy logic Langkah-langkah 1.1. Contrast Improvement with INT- Operator Langkah: a.menentukan fungsi membership b.Mengubah nilai membership c.Membuat skala warna gray

  15. fuzzy logic 1.2. Contrast Improvement using Fuzzy Expected Value (Craig and Schneider 1992) 1. Step: Calculate the image histogram 2. Step: Determine the fuzzy expected value (FEV) 3. Step: Calculate the distance of gray-levels from FEV 4. Step: Generate new gray-levels

  16. fuzzy logic 1.3. Contrast Improvement with Fuzzy Histogram Hyperbolization (Tizhoosh 1995/1997) 1. Step: Setting the shape of membership function (regrading to the actual image) 2. Step: Setting the value of fuzzifier Beta (a linguistic hedge) 3. Step: Calculation of membership values 4. Step: Modification of the membership values by linguistic hedge 5. Step: Generation of new gray-levels

  17. fuzzy logic 1.4. Contrast Improvement based on Fuzzy If-Then Ruels (Tizhoosh 1997) • Step: Setting the parameter of inference system (input features, membership functions,..) • Step: Fuzzification of the actual pixel (memberships to the dark, gray and bright sets of pixels) .

  18. fuzzy logic 1.4. Contrast Improvement based on Fuzzy If-Then Ruels (Tizhoosh 1997) 3. Step: Inference (e.g. if dark then darker, if gray then gray, if bright then brighter) 4. Step: Defuzzification of the inference result by the use of three singletons

  19. fuzzy logic 1.5. Locally Adaptive Contrast Enhancement (Tizhoosh et al. 1997) • In many cases, the global fuzzy techniques fail to deliver satisfactory results. Therefore, a locally adaptive implementation is necessary to achieve better results. See some examples and a comparison with calssical approach.

  20. fuzzy logic

  21. fuzzy logic

  22. fuzzy logic

  23. fuzzy logic

  24. fuzzy logic Deteksi Tepi • Perbaiki dengan rumus di bawah

  25. fuzzy logic Deteksi Tepi

  26. fuzzy logic Contoh Hasil Deteksi Tepi

  27. fuzzy logic Segmentasi Image dengan Fuzzy

  28. fuzzy logic Segmentasi Image dengan Fuzzy

  29. fuzzy logic

  30. fuzzy logic Contoh segmentasi

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