Automated Screen Damage Detection for Smartphones

Seasia Infotech partnered with a leading refurbished phone enterprise to design an AI-based mobile screen inspection for refurbishment that streamlines quality control for warehouses and repair centers. The client aimed to replace error-prone manual inspections with a mobile screen grading system powered by computer vision, multi-angle CCD imaging, and deep learning models.

The goal: achieve 90%+ accurate phone screen crack detection, reduce operational costs, and scale mobile device quality control across thousands of devices.

Schedule a Call

Project Overview

INDUSTRY

Mobile Screen Damage detection

PROJECT DURATION

4–6 Months

The refurbished device market suffers from delays and inconsistencies in manual phone repair inspection systems. Inspectors often miss micro-cracks or grade severity inconsistently, leading to disputes, returns, and slow refurbishment cycles.

Seasia Infotech developed a deep learning screen damage detection solution designed as a scalable automated phone screen crack detection system for warehouses. The system combines multi-angle phone inspection systems, RGB → HSI transformations, and CNN-based object detection systems for smartphone screen defects to accurately classify cracks into minor, moderate, and severe categories.

Project Overview

INDUSTRY

Mobile Screen Damage detection

PROJECT DURATION

4–6 Months

INDUSTRY

Mobile Screen Damage detection

PROJECT DURATION

4–6 Months

Project Scope & Challenges

The client needed a mobile device quality control solution to automate screen defect detection across different models and volumes, overcoming manual inspection limits.

Subtle Damage

Cracks visible only at certain angles

Model Variability

Different sizes and materials

High Throughput

Inspecting thousands daily

Manual Limitations

Inconsistent and costly checks

Seasia’s Solution

By engineering an AI-driven mobile device repair automation platform through its Artificial Intelligence services , Seasia transformed phone inspection into a fast, scalable process.

Multi-Angle CCD Camera System for Phone Screen Inspection to capture every defect

RGB → HSI Color Transformation to enhance defect visibility.

Deep Learning & Object Detection models for detecting minor, moderate, and major screen damage automatically.

Customizable Training Tools allowing clients to upload datasets for new models.

Automated Mobile Screen Grading System for severity classification

Technology Stack

Frontend

CCD Cameras

Image Preprocessing Techniques

Backend

Deep Learning

Computer Vision Models (CNNs)

APIs / Services

Nanonets API

OCR Integration

Data Processing

RGB → HSI

Noise Reduction

Angle & Lighting Correction

Results & Achievements

90%+ Accuracy
AI for phone screen inspection across 200,000+ devices
3× Faster Throughput
compared to manual inspections
Cross-Model Adaptability
across multiple brands and phone types
Cost Savings
via reduced manpower dependency
Reliable Mobile Screen Damage Detection
that cut disputes and returns

Transforming Refurbished Phone Quality Control with AI

Seasia’s automated screen inspection demonstrates how mobile screen damage detection powered by AI can reshape the used phone refurbishment technology sector. By combining deep learning, multi-angle phone inspection systems, and customizable training datasets, Seasia delivered a solution that accelerates inspections, boosts accuracy, and ensures consistent grading at scale.

Connect with Our Team

What They Say

A unified, enterprise-grade suite of proprietary AI tools that accelerates software delivery, enhances system reliability, and significantly reduces time A unified, enterprise-grade suite of proprietary AI tools that accelerates software delivery, enhances system reliability, and significantly. Read More