This week was mainly about stepping back and rethinking the scan subsystem so it’s realistic and achievable within our timeline. After looking more closely at what it would take to build a fully custom OMR pipeline, I decided to revise the architecture to something more modular and practical. Instead of implementing staff detection and symbol recognition from scratch, I restructured the scan layer into three parts: preprocessing, third-party OMR execution, and postprocessing. This change reduces risk and gives us more flexibility to focus on higher-impact features later.
Planning & Architecture Refinement
A large part of the week went into refining the scan pipeline design and updating our system diagrams to reflect that change. I clarified how image normalization feeds into the OMR engine, and how the raw MusicXML output will be validated and cleaned before being used downstream.
This week I clarified the following pipeline stages:
- Image normalization and geometric correction
- Quality-based input filtering
- OMR engine execution
- MusicXML parsing and structural validation
During this process, I also worked on completing the design presentation with my teammates in refining our user requirements, design requirements, solution approach, and our overall schedule and approach.
Initial Normalization Implementation
I began implementing the preprocessing stage using OpenCV in Python. So far, I’ve put together the basic structure of the normalization pipeline, including:
- Detecting the page contour and applying perspective warping
- Estimating and correcting skew using Hough line detection
- Applying contrast enhancement (CLAHE)
- Adding preliminary blur detection using Laplacian variance
The pipeline is partially implemented and producing intermediate debug outputs so I can see how each stage behaves. I’m still tuning parameters and testing on different sheet music images to make sure the behavior is consistent.
Schedule
I’m currently on schedule. The architecture change actually reduces complexity and makes the scan layer more manageable moving forward. There are no major blockers right now.
Deliverables for Next Week
Next week I plan to connect the normalization output to the OMR execution step and start integrating basic MusicXML parsing and validation. I’ll also continue refining the preprocessing parameters using additional test images.
Part A
On the topic of public health, safety, and overall welfare, the system we are building is designed to be safe, low-risk and supportive for users. Specifically on the safety side, the system operates using low-voltage microcontroller hardware and LED components which minimizes electrical hazard. The bluetooth communication between the hardware and software also follows standard protocols and is not exposed to high-power components. From a health and well-being perspective, the system is designed to create a positive learning experience where feedback is structured and is not overwhelming for the user. The guided playing modes are intended to give users more freedom to choose how to practice rather than cause unnecessary stress. There is also not personal data being transmitted externally and therefore, overall the system is built to be safe, accessible, and supportive for beginners at different skill levels