Please enable JavaScript.
Coggle requires JavaScript to display documents.
Image Acquisition Conditions and Their Impact on Image Processing and…
Image Acquisition Conditions and Their Impact on Image Processing and Application Performance
Image Acquisition Conditions
Illumination Conditions
Light Intensity
Underexposure
Overexposure
Light Direction
Shadows
Natural Lighting
Artificial Lighting
Camera Parameters
Exposure Time
Aperture
Shutter Speed
ISO Sensitivity
White Balance
Lens Properties
Focus
Focal Length
Optical Zoom
Depth of Field
Lens Distortion
Sensor Characteristics
CCD Sensor
CMOS Sensor
Pixel Size
Dynamic Range
Signal-to-Noise Ratio
Environmental Factors
Weather Conditions
Fog
Rain
Dust
Camera Motion
Object Motion
Image Quality Effects
Brightness
Controlled by Illumination and Exposure
Contrast
Affected by Lighting and Dynamic Range
Sharpness
Affected by Focus and Lens Quality
Resolution
Determines Detail Visibility
Noise
Increased by High ISO and Sensor Limitations
Blur
Motion Blur
Defocus Blur
Color Accuracy
Controlled by White Balance and Sensor Response
Downstream Image Processing
Image Enhancement
Contrast Enhancement
Histogram Equalization
Sharpening
Noise Reduction
Gaussian Filtering
Median Filtering
Bilateral Filtering
Image Restoration
Deblurring
Distortion Correction
Color Correction
Feature Extraction
Edge Detection
Texture Features
Shape Features
Keypoint Detection
Segmentation
Thresholding
Region-Based Methods
Deep Learning Segmentation
Recognition
Object Detection
Classification
Tracking
Application Performance
Medical Imaging
Disease Detection
MRI Analysis
X-ray Diagnosis
Autonomous Vehicles
Object Detection
Lane Detection
Traffic Sign Recognition
Surveillance Systems
Face Recognition
Person Tracking
Security Monitoring
Remote Sensing
Satellite Image Analysis
Land Classification
Environmental Monitoring
Industrial Vision
Quality Inspection
Defect Detection
Automated Manufacturing
Cause–Effect Relationships
Poor Lighting
→ Low Contrast
→ Difficult Feature Extraction
→ Lower Recognition Accuracy
High ISO
→ Increased Noise
→ Reduced Image Quality
→ Processing Errors
Camera Motion
→ Motion Blur
→ Feature Loss
→ Detection Failure
Incorrect Focus
→ Blurred Image
→ Poor Segmentation
→ Reduced Accuracy
High Resolution
→ More Details
→ Better Recognition
→ Increased Storage and Processing Cost
Good Acquisition Conditions
→ High Image Quality
→ Reliable Processing
→ Better Application Performance
Performance Evaluation
Accuracy
Precision
Recall
F1 Score
Processing Speed
Robustness
Literature Foundations
Gonzalez & Woods
Image Formation
Sampling
Noise
Enhancement
Richard Szeliski
Camera Models
Image Formation
Feature Extraction
Computer Vision Pipeline
Burger & Burge
Digital Image Acquisition
Camera Systems
Image Quality
Anil K. Jain
Pattern Recognition
Feature Analysis
Classification