How to Choose Image Data Formats? Decode the Underlying Logic of Sensor Output-Knowledge Encyclopedia-Shenzhen Kai Mo Rui Electronic Technology Co. LTD

How to Choose Image Data Formats? Decode the Underlying Logic of Sensor Output

Source：Shenzhen Kai Mo Rui Electronic Technology Co. LTD2026-05-26

Industrial machine vision systems are core technologies for modern automated inspection, recognition, measurement and positioning. The selection of image sensors and their output formats directly affect the system's accuracy, real-time performance and processing efficiency. Combining mainstream formats including YUV, RGB, RAW and JPEG, this article makes an in-depth analysis of their applications and differences in industrial vision.

1. Image Processing Workflow in Industrial Vision

The standard image acquisition and processing workflow for industrial vision systems is as follows:

Sensor Acquisition → Data Output (YUV/RGB/RAW/JPEG) → Image Processing (Edge Detection, Recognition, Measurement) → Control & Decision

Therefore, the data format output by the sensor determines the performance, algorithm complexity and final accuracy of subsequent processing.

2. YUV Format: Suitable for Video Streaming, Not the Mainstream for Industrial Use

Features

YUV separates an image into luminance (Y) and chrominance (UV) components.

YUV422 is the most commonly used type. Two pixels share one set of UV data to reduce bandwidth occupancy.

It is widely used for video transmission and low-latency display.

Application Scenarios in Industrial Vision

Vision-guided robots: Scenarios demanding high real-time performance with general image quality requirements
Basic inspection: Presence/absence detection, QR code scanning

Drawbacks

Color compression leads to data loss.

It is not applicable to precision measurement or scenarios requiring high color accuracy.

3. RGB Format: Convenient for Direct Display with Severe Data Compression

Typical Format: RGB565

It is a 16-bit format (5 bits for Red, 6 bits for Green, 5 bits for Blue), mainly adopted for screen display on low-end devices.

Deficiencies in Industrial Vision

Insufficient color accuracy makes it unfit for professional image analysis.

Noticeable color deviation between pixels will interfere with edge detection and color segmentation.

Conclusion

RGB565 is rarely used for industrial image analysis, and is only applied for debugging and display.

4. RAW Format: The Top Choice for Industrial Vision

What is RAW

RAW refers to the original signal output by the image sensor. Each pixel corresponds to a single color channel (R/G/B) and is arranged in Bayer patterns such as BGGR and GRBG.

Operations including color interpolation, white balance and noise reduction need to be completed via software or hardware ISP (Image Signal Processor).

Why RAW Is Widely Adopted in Industrial Vision

Lossless data retention: Users can fully customize the processing flow to match diverse algorithm requirements.
Stable image consistency: Free from discrepancies caused by proprietary JPEG algorithms of different sensor manufacturers.
Ideal for high-resolution cameras: Especially prevalent for sensors with 5MP and above resolution.

Application Cases

PCB inspection & surface defect detection: Scenarios requiring rich grayscale details
Color analysis & coating inspection: Enables accurate restoration of original colors
Metrology-level vision: High-precision detection for dimension, angle and deformation measurement

5. JPEG Format: Storage-Optimized but Limited in Precision

Features

Sensors come with built-in JPEG encoders to output compressed images. The compact data size facilitates transmission and storage.

Limitations in Industrial Scenarios

Lossy compression causes permanent loss of image details.

Unstable image consistency makes it incompatible with machine learning and algorithms that rely on high precision.

Applicable Scenarios

Non-real-time quality traceability: Archiving captured product images
Lightweight cloud analysis: Transmitting images from edge devices to the cloud for simple processing

6. Significance of RAW and Bayer Pattern

Industrial vision systems require full control and thorough analysis of every pixel:

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