Manual
Table Of Contents
- 1. Updates
- 2. Product Introduction
- 3. Software Interface
- 3.1 Welcome Page
- 3.2 Home Page
- 3.3 Menu
- 3.4 Control Toolbar
- 3.5 Tool Box
- 3.6 Result Display
- 3.7 Flow Management
- 3.8 Camera Management
- 3.9 Controller Management
- 3.10 Global Variables
- 3.11 Communication Management
- 3.12 Global Trigger
- 3.13 Global Script
- 3.14 Operation Interface
- 3.15 Data Queue
- 3.16 Flow Time
- 3.17 Dobot Panel
- 4. Vision Tools
- 4.1 Acquisition
- 4.2 Location
- 4.2.1 Feature Match
- 4.2.2 Greyscale Match
- 4.2.3 Mark Location
- 4.2.4 Circle Search
- 4.2.5 Line Search
- 4.2.6 Blob Analysis
- 4.2.7 Caliper
- 4.2.8 Edge Search
- 4.2.9 Position Correction
- 4.2.10 Rect Search
- 4.2.11 Peak Search
- 4.2.12 Edge Intersection
- 4.2.13 Parallel Lines Search
- 4.2.14 Quadrilateral Search
- 4.2.15 Line Group Search
- 4.2.16 Multi-line Search
- 4.2.17 Blob Label Analysis
- 4.2.18 Path Extraction
- 4.2.19 Find Angle Bisector
- 4.2.20 Find Median Line
- 4.2.21 Calculate Parallel Lines
- 4.2.22 Find Vertical Line
- 4.3 Measurement
- 4.4 Image Generation
- 4.5 Recognition
- 4.6 Deep Learning
- 4.7 Calibration
- 4.8 Calculation
- 4.9 Image Processing
- 4.9.1 Image Combination
- 4.9.2 Image Morphology
- 4.9.3 Image Binarization
- 4.9.4 Image Filter
- 4.9.5 Image Enhancement
- 4.9.6 Image Computing
- 4.9.7 Distortion Correction
- 4.9.8 Image Clarity
- 4.9.9 Image Fixture
- 4.9.10 Shade Correction
- 4.9.11 Affine Transformation
- 4.9.12 Ring Expansion
- 4.9.13 Copy and Fill
- 4.9.14 Frame Mean
- 4.9.15 Image Normalization
- 4.9.16 Image Correction
- 4.9.17 Geometric Transformation
- 4.9.18 Image Stitch
- 4.9.19 Multiple Images Fusion
- 4.10 Color Processing
- 4.11 Defect Detection
- 4.11.1 OCV
- 4.11.2 Arc Edge Defect Detection
- 4.11.3 Linear Edge Defect Detection
- 4.11.4 Arc-Pair Defect Detection
- 4.11.5 Line-Pair Defect Detection
- 4.11.6 Edge Group Defect Detection
- 4.11.7 Edge Pair Group Defect Detection
- 4.11.8 Edge Model Defect Detection
- 4.11.9 Edge Pair Model Defect Detection
- 4.11.10 Defect Contrast
- 4.12 Logic Tools
- 4.13 Communication
- 4.14 Dobot Magician Tools
- 5. Cases
- 6. Dobot Magician Demo
DobotVisionStudio User Guide
Issue V4.1.2 (2022-06-08) User Guide Copyright © Yuejiang Technology Co., Ltd.
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When the grayscale difference between the character and the background is small, it is
recommended to enable binary image. When the font is inclined or the automatic segmentation is
inaccurate, it is recommended to manually select characters and use default parameters for training
parameters. After selection, click the training template to create character outline, and click next to
enter the training interface as shown below.
You need to train about 10 OK characters on the training interface. For NG images marked with red
dots, you need to select "not count current image", and click OK to complete the training.
After the training is completed, the detection effect is verified and debugged. When the false
detection occurs, you can refer to section OCV to adjust parameters.