ReMo Prototype: Table of Contents Scanner
Collaborators: Ryan Moore & Keegan Moseley
Encouraging Reading Through Technology
ReMo is a Maine-based tech startup focused on improving literacy rates among students. During my final semester of graduate school, my classmate Keegan Moseley and I collaborated with the ReMo team to design a prototype that helps students track the books and articles they read outside of class.
The goal was simple but powerful: make it easy—and even fun—for students to record what they’re reading so teachers could measure progress over time.
The Challenge
Teachers often struggle to track extracurricular reading and understand how students are engaging with texts beyond assigned material. ReMo wanted a way to automatically capture what students were reading while keeping the process effortless for kids of all ages.
Our Solution
We developed a computer vision–based prototype that allows students to snap a photo of a book’s table of contents and extract useful information—like titles and authors—using OpenCV and PyTesseract OCR.
Inspired by mobile banking’s check deposit workflow, our design walks students through a few simple steps:
- Take a photo of the table of contents
- Crop and straighten the image
- Detect and clean text regions
- Extract titles with OCR
- Review and confirm results
The app then organizes the extracted text into a clean, hierarchical structure, ready to be submitted or logged for teacher review.
Technical Highlights
This prototype was built as a Streamlit web app and demonstrates a full preprocessing and OCR pipeline for educational data capture.
Tech Stack
| Layer | Tools / Libraries |
|---|---|
| Framework | Streamlit (Python) |
| Computer Vision | OpenCV, SciPy |
| OCR | PyTesseract |
| Data Processing | NumPy, Pandas |
| UI Components | streamlit_drawable_canvas, st_aggrid, PIL |
Impact
The Table of Contents Scanner showcased how simple computer vision tools could support literacy tracking in a fun, approachable way. It offered ReMo a practical foundation for expanding their reading engagement platform with image-based input and real-time feedback loops for students.
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