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Tahmid Tanjim RahimMobile App Developer
Mobile App Case Study

AI Vision Scanner / OCR

Mobile document scanner and optical character recognition utility app.

ClientIndependent Project
RoleMobile App Developer
TimelineMilestone Phased Builds
PlatformCross-Platform (Flutter)
Stack:FlutterDartOn-Device OCR
01

The Problem

Manual document transcription and receipt scanning are prone to input mistakes and data security concerns when sending private records to cloud APIs. This utility provides professionals with an on-device camera scanner that instantly isolates documents, runs local optical character recognition, and exports clean formatted text without cloud dependency.

02

What I Built

Delivered end-to-end in milestone phases, with a verified working build at each stage and full source code handover.

Real-time camera document viewfinder with edge detection and perspective correction
On-device optical character recognition detecting text blocks with high accuracy
Interactive text extraction bottom sheet allowing inline edits and cleanup
One-tap export options to searchable PDF and formatted TXT files
Local history storage for scanned documents and invoices
03

Key Technical Decisions

On-Device Machine Learning: Utilized local on-device ML Kit vision models for zero-latency scanning without sending private documents over external servers.

Reactive Camera Bridging: Implemented high-performance Flutter camera stream listeners for real-time bounding box rendering.

04

Results & Client Impact

Engineered an offline-first mobile utility achieving sub-second text recognition from receipts, invoices, and business contracts.

06

Application Gallery

Verified production screens from the Barrera's Remodeling Inc Flutter application.

AI Vision Scanner OCR Screen

AI Vision Scanner - Document detection and structured text extraction