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Simplified Musical Notation Recognition: A Step-by-Step Approach

This project explores the recognition of simplified musical notation, emphasizing its popularity and accessibility for music learners and composers. We employ several methods for effective processing, starting with image preprocessing to eliminate noise and simplify the image using techniques like Otsu's method for binarization. The project progresses through cutting lines, dividing notations, and feature extraction, ultimately leading to the identification of musical instruments and matching notes. Key demos include classic songs like "Twinkle, Twinkle, Little Star."

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Simplified Musical Notation Recognition: A Step-by-Step Approach

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  1. Team30 陳育修蘇裔彥 Dipfinalproject簡譜辨識

  2. why 簡譜辨識？ • popularandwidelyused • morepeopleshowtheirmusictalent • easyforpeopletolearnnewsongs • from beginner • to become a composer !

  3. somemethods • Step1:(preprocessing) • loadjpeg • clean noise • simplify the image • method 1 : use QT as good tool • > easy for RGB processing • method 2 : convert jpg to simple format /ex:ppm / • > Otsu method for binarization

  4. Otsu’s way to determine T* • T *的決定會滿足C1和C2之間的變異數(Between- variance)為最大 • [or Within-variance 之和為最小。] • W1=pro in C1σ1 = expectation in C1 • σw2=W1σ12 +W2σ22 σB2=W1(u1-uT*)2 +W2(u2-uT*)2 • σw2 +σB2 = Cons.

  5. Original : • Processed :

  6. somemethods • Step2: • cutlines • >easyforcleanpicture • >cleandirtypicture… • dividenotationsandconquerthem • >recursivelyfindconnectedcomponent

  7. somemethods • Step3: • makesomefeatures • >cutnotationintopiecesandanalyze • traindata • >SVM

  8. somemethods • Step4: • To pick up certain musical instruments • Match the notes and finally plays !

  9. Demo • Little star • Little bee

  10. Vision • Hand written notes • Multi-channel midi • Special notes ( 滑音 …)

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