Detecting, Extracting and Merging Receipts from Uploaded Smartphone Images

Sensibill provides financial tools like digital receipt data that help banks and credit unions better know and serve their customers. Users can upload digital images through tools and the company would do image processing first and then use processed images to analyze. However, the previous image processing algorithm is time-consuming for users and doesn’t satisfy the use case of long receipts that don’t fit on a single image. The project is aimed to build a method that can efficiently generate one clear final image from multiple uploaded images.

Faculty Supervisor:

Lueder Kahrs;Michael Guerzhoy

Student:

Partner:

Sensibill Inc

Discipline:

Computer science

Sector:

Information and cultural industries

University:

University of Toronto

Program:

Accelerate

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