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I-DV: Deep Learning Vision Inspection System

Human-Like Inspection Without the Human Factor

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The BOS I-DV is a configurable, vision inspection system that allows manufacturers to harness the power of deep learning technology to solve quality inspections too complicated, time consuming, and costly to program using traditional rules-based algorithms. Realize the reliability, accuracy, and enhanced quality of automating inspections once reserved for manual operators.


Throughout the modern manufacturing plant, various inspections have traditionally been reserved for manual operators due to automation challenges because of the complexity or variation.  The introduction of deep learning technology has enabled these inspections to be automated and performed reliably at a higher degree of accuracy than ever before.

I-DV Automotive Quality Inspection


The BOS I-DV is a turnkey, deep learning machine vision system. Powered by Cognex ViDi™, the I-DV is designed for industrial image analysis and configurable for your application.

I-DV Deep Learning Vision Inspection panel

Pre-Engineered Design for Low Cost & Quick Delivery
Easy to Deploy & Maintain
User Friendly HMI
CSA Safety Compliant Design
Training & Support

Supports up to 8 Cameras
Supports up to 32 Acquisitions/Camera
Supports up to 16 Inspections/Acquisition
Parallel Image Acquisition & Processing
Communication: Ethernet/IP or Profinet
Input Power: 120V
    Deep Learning Defect Detection
    Deep Learning Assembly Verification
    Deep Learning OCR
    Deep Learning Option Classification
    Traditional Machine Vision Tools

Industrial Vision Controller & Panel Stand
Cognex ViDi License
GigE Vision Camera(s), Lens(es), Filter(s)
Lighting & Adjustable Mount for Each Camera
Operator Interface
Peripheral Accessories (Keyboard & Tray, Mouse)
Controls Training (3-Day BOS Curriculum)

Part Fixture & Tooling
Additional Camera Capacity
Upgraded Vision Controller
Enhanced Programming Customization
Alternative Communication Protocols
Line Scan or 3D Profiler Package
Peripheral Accessories (Keyboard & Tray, Mouse)
Camera Mounting Structure

Applications & Case Studies

I-DV Capabilities

Accurately accomplish complex defect detection. Through deep learning, the system can be trained to discern between acceptable variations and defects, even in situations where the parts and/or defects can vary in size or appearance.

Machined Parts Defect Detection Case Study

Weld Quality Defect Detection Case Study

Seat Wrinkle Defect Detection Case Study

Read skewed, highly deformed, low-contrast or poorly etched code with ease. Through deep learning, the system is trained on the actual text being used in the application, allowing the system to read codes that would be next to impossible with traditional optical code recognition (OCR) tools.

Detect if components are installed and assembled correctly even if components change slightly in appearance, colour, size angle or shape.


Determine if the correct option is installed even if the option varies in appearance, colour, size, angle, shape or one or more options have subtle differences.

Exterior Trim Option Classification Case Study

Benefits of Deep Learning Inspection

Deep Learning Inspection process

Deep learning combines the self-learning and discernment capability of human inspection with the speed and consistency of a computerized system

Deep learning learns what is right and wrong based on sample images, similar to how one would teach a human inspector. However, unlike human inspectors, deep learning is a computerized system and not subject to the errors or inconsistencies of human inspection. Through deep learning, the BOS I-DV is able to complete more complex inspections with a higher degree of accuracy for automated inspection than ever before.

Traditional Machine Vision Human Inspection Deep Learning Inspection
Type Rules Based - Traditional Machine Vision is programmed by setting up tools that must meet certain thresholds or percentages Learns by Example - Quality control operators are shown the difference between defective and good parts Self-Learning - Deep Learning learns from sample images thus being able to discern between acceptable variations and defects
Speed Fast - Typical inspections take 1-3 seconds Slow, Inconsistent - Inspection times are typically 5-10 seconds Fast - Images are acquired by cameras and analyzed using processors
Reliability/Accuracy Reliable, High Accuracy Rate Achievable - Quantitative measurements are computed on every inspection Inconsistent, Lower Accuracy - Defects can be missed depending on the skill of the current operator Reliable, High Accuracy Rate Achievable - Images are always processed by the same algorithm
Complexity/Variation Unable to manage complex or highly variable inspections - Traditional machine vision rules-based algorithms are not able to easily manage complex inspections Able to handle large variability and complexity - Human operators have the ability to recognize defects in variable or complex inspections Designed to handle variability and complexity - Deep learning thrives in accurately discerning acceptable variations even in the most complex inspections


Contact us today for more information, including pricing. We look forward to collaborating with you.

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