Computer Vision for Industry Applications Training Course

Module 1: Image Processing Fundamentals and Optics

• Digital image representation: Pixel formats, color spaces (RGB, HSV, Grayscale), and bit depth
• Understanding industrial optics: Lens selection, focal length, and field of view (FOV)
• Lighting techniques for industry: Backlighting, structured light, and ring illumination
• Pre-processing techniques: Noise reduction filters, Gaussian blur, and morphological operations
• Image thresholding and binarization for region-of-interest extraction
• Practical session: Configuring a camera and applying filtering techniques to enhance contrast on industrial parts

Module 2: Feature Extraction and Descriptor Matching

• Geometric transformations: Rotation, scaling, and perspective correction (warping)
• Corner detection using Harris and Shi-Tomasi algorithms
• Advanced feature descriptors: Understanding SIFT, SURF, and ORB for object recognition
• Feature matching techniques: Brute-Force vs. FLANN-based matchers
• Implementing RANSAC for robust outlier rejection in cluttered environments
• Practical session: Building an automated logo detection system using feature matching

Module 3: Object Detection and Localization

• The evolution of detection frameworks: From Haar Cascades to modern neural networks
• Understanding Bounding Boxes, Anchors, and Intersection over Union (IoU) metrics
• Architecture of Single-Shot Detectors (SSD) and the YOLO (You Only Look Once) family
• Data annotation strategies: Using tools like CVAT or LabelImg for industrial datasets
• Post-processing: Implementing Non-Maximum Suppression (NMS) to eliminate duplicate detections
• Practical session: Training a custom YOLOv8 model to detect and count mechanical components on a conveyor belt

Module 4: Deep Learning for Image Classification

• Fundamentals of Convolutional Neural Networks (CNNs): Kernels, strides, and pooling
• Benchmarking standard architectures: VGG, ResNet, and EfficientNet
• The power of Transfer Learning: Adapting pre-trained models for specific industrial tasks
• Optimization strategies: Learning rate scheduling, early stopping, and weight decay
• Performance evaluation using Confusion Matrices and F1-Scores
• Practical session: Implementing a classifier to categorize electronic components (resistors, capacitors, ICs)

Module 5: Semantic and Instance Segmentation

• Pixel-level classification: Understanding Semantic vs. Instance Segmentation
• Architecture of U-Net for precise industrial masking and measurement
• Mask R-CNN: Combining object detection with pixel-wise mask generation
• Use cases for segmentation: Measuring surface area and identifying liquid levels in bottling
• Evaluating segmentation performance using the Dice Coefficient and Jaccard Index
• Practical session: Developing a segmentation model to precisely outline and measure agricultural produce

Module 6: Real-time Video Analysis and Motion Tracking

• Handling video streams: Frame rate management and buffering strategies
• Background subtraction techniques for static camera monitoring
• Optical Flow: Tracking pixel movement between consecutive frames
• Object tracking algorithms: Centroid tracking and the DeepSORT framework
• Event triggering: Counting objects crossing a virtual boundary in real-time
• Practical session: Implementing a real-time worker safety system that detects proximity to dangerous machinery

Module 7: Industrial Quality Inspection and Defect Detection

• Identifying anomalies: Cracks, scratches, and missing components on surfaces
• Comparative analysis: Golden image subtraction vs. AI-driven anomaly detection
• Using Autoencoders for unsupervised defect detection in uniform materials
• Integrating OCR (Optical Character Recognition) for serial number and label verification
• Statistical Process Control (SPC) integration using vision system data
• Practical session: Building a defect detection pipeline for quality control on a printed circuit board (PCB)

Module 8: 3D Vision and Depth Estimation

• Basics of Stereo Vision: Disparity mapping and depth from triangulation
• Introduction to Time-of-Flight (ToF) and Structured Light sensors
• Processing Point Clouds: Filtering, downsampling, and surface reconstruction
• Bin picking applications: Estimating 6D pose for robotic arm interaction
• Calibrating 2D images with 3D spatial coordinates
• Practical session: Calculating the volume of an object using a depth camera and point cloud analysis

Module 9: Edge AI and Hardware Optimization

• Constraints of industrial edge deployment: Latency, power, and connectivity
• Model compression techniques: Pruning, Quantization, and Knowledge Distillation
• Deploying on Nvidia Jetson: Utilizing TensorRT for high-speed inference
• Overview of OpenVINO for optimizing vision models on Intel hardware
• Containerization of vision applications using Docker for rapid deployment
• Practical session: Quantizing a trained model and deploying it onto an edge device for real-time inference

Module 10: Computer Vision System Integration and Ethics

• Communication protocols: Modbus, OPC-UA, and MQTT for PLC/SCADA integration
• Designing robust User Interfaces (UI) for operators on the factory floor
• Security in vision systems: Data privacy and protecting intellectual property
• Ethical considerations: Surveillance bias and facial recognition policies
• Maintaining and scaling vision systems: Version control and model monitoring
• Practical session: Designing a system architecture that sends a "Stop" signal to a simulated PLC upon detecting a defect

Requirements:

Participants should be reasonably proficient in English.

Applicants must live up to Armstrong Global Institute admission criteria.

Terms and Conditions

1. Discounts: Organizations sponsoring Four Participants will have the 5th attend Free

2. What is catered for by the Course Fees: Fees cater for all requirements for the training – Learning materials, Lunches, Teas, Snacks and Certification. All participants will additionally cater for their travel and accommodation expenses, visa application, insurance, and other personal expenses.

3. Certificate Awarded: Participants are awarded Certificates of Participation at the end of the training.

4. The program content shown here is for guidance purposes only. Our continuous course improvement process may lead to changes in topics and course structure.

5. Approval of Course: Our Programs are NITA Approved. Participating organizations can therefore claim reimbursement on fees paid in accordance with NITA Rules.

Booking for Training

Simply send an email to the Training Officer on training@armstrongglobalinstitute.com and we will send you a registration form. We advise you to book early to avoid missing a seat to this training.

Or call us on +254720272325 / +254725012095 / +254724452588

Payment Options

We provide 3 payment options, choose one for your convenience, and kindly make payments at least 5 days before the Training start date to reserve your seat:

1. Groups of 5 People and Above – Cheque Payments to: Armstrong Global Training & Development Center Limited should be paid in advance, 5 days to the training.

2. Invoice: We can send a bill directly to you or your company.

3. Deposit directly into Bank Account (Account details provided upon request)

Cancellation Policy

1. Payment for all courses includes a registration fee, which is non-refundable, and equals 15% of the total sum of the course fee.

2. Participants may cancel attendance 14 days or more prior to the training commencement date.

3. No refunds will be made 14 days or less before the training commencement date. However, participants who are unable to attend may opt to attend a similar training course at a later date or send a substitute participant provided the participation criteria have been met.

Tailor Made Courses

This training course can also be customized for your institution upon request for a minimum of 5 participants. You can have it conducted at our Training Centre or at a convenient location. For further inquiries, please contact us on Tel: +254720272325 / +254725012095 / +254724452588 or Email training@armstrongglobalinstitute.com

Accommodation and Airport Transfer

Accommodation and Airport Transfer is arranged upon request and at extra cost. For reservations contact the Training Officer on Email: training@armstrongglobalinstitute.com or on Tel: +254720272325 / +254725012095 / +254724452588