Structured Light vs LiDAR: Differences, Applications, and How They Work

1. From Everyday Devices to 3D Data Capture

Before exploring the technologies themselves, it helps to understand what 3D data capture means. 3D data capture is the process of measuring the shape, depth, or spatial position of real-world objects and environments and converting that information into digital 3D data.

Depending on the technology and application, the output may include:

• A point cloud containing millions of measured 3D points

• A 3D mesh that represents an object’s surface

• A depth map that records the distance between a sensor and a scene

• A digital 3D model used for visualization, inspection, design or analysis

Many people encounter 3D capture technology without realizing it. Some smartphones use depth-sensing technologies to support facial recognition or augmented reality. Professional 3D scanners capture detailed object geometry for reverse engineering and quality inspection. LiDAR systems can measure large environments and help vehicles, robots, and mapping systems understand the space around them.

Although these systems may look very different, they share a common goal:

To convert physical objects and environments into usable digital 3D data.

2. How Structured Light Captures 3D Data

How Does Structured Light Work?

Structured light 3D scanning works by projecting a known pattern of light onto an object and analyzing how that pattern changes across the object’s surface.

The process generally follows four steps:

1. A projector casts a known light pattern onto the object.

2. The pattern appears distorted or deformed as it follows changes in the object’s shape.

3. One or more cameras capture the deformed pattern.

4. Software compares the projected pattern with the captured pattern and calculates the 3D position of points on the surface.

Using a smartphone LiDAR app to create a 3D scan of a sculpture

LiDAR at a Larger Scale

The same fundamental principle can be expanded to much larger systems. Professional LiDAR technologies are widely used in:

• Autonomous vehicles

• Robotics

• Mobile mapping

• Surveying

• Architecture and construction

• Infrastructure documentation

• Environmental mapping
  
  

For example, a vehicle-mounted LiDAR system can capture roads, buildings, vegetation, and other surrounding features. A robot can use LiDAR data to detect obstacles and understand the space around it. LiDAR is not limited to one industry. Its value comes from its ability to measure distances and create large-scale spatial datasets efficiently.

LiDAR technology used for terrain surveying and large-scale landscape mapping

When Is LiDAR a Good Choice?

LiDAR is often well suited to applications that require broad coverage or long-range spatial measurement. It may be a good choice when you need:

• Large-area 3D data

• Long-range depth measurement

• Room, building, or street-level capture

• Environmental mapping

• Spatial awareness

• Navigation or autonomous perception

4. Structured Light vs LiDAR: What’s the Difference?

Both structured light and LiDAR can capture 3D data, but they use different measurement principles and are often optimized for different tasks.

The biggest difference is not simply that one technology is “more accurate” than the other. Instead, they are generally designed to answer different measurement needs:

Structured light is often optimized for capturing detailed object geometry, while LiDAR is often optimized for measuring distance and understanding larger spatial environments.

5. Combining Large-Scale LiDAR Data with Detailed 3D Scanning

Structured light excels at capturing highly detailed object geometry, while LiDAR is optimized for measuring large environments. In this guide, you'll learn how each technology works, their key differences, and when to use one—or combine both—for 3D data capture.

Why Combine LiDAR and 3D Scanning?

LiDAR captures large environments well, but often lacks fine object detail. 3D scanning can fill this gap by adding high-resolution geometry for specific objects. Together, they provide:

• LiDAR: overall spatial context

• 3D scanning: detailed object geometry

• Combined result: a more complete 3D dataset

Adding Detailed 3D Geometry with EinScan Libre

SHINING 3D’s EinScan Libre is a wireless, standalone 3D scanner designed for flexible 3D capture. Depending on the scanning mode and workflow, it can capture objects ranging from small parts to large structures.

EinScan Libre also supports exporting scan data in formats such as LAS, a widely used point-cloud format for large-scale and georeferenced datasets. By exporting detailed scan data in LAS format, users can import it into compatible point-cloud software and combine it with LiDAR datasets.

This workflow makes it possible to preserve both the broader spatial context captured by LiDAR and the detailed geometry captured by 3D scanning.

To learn more about LAS and other common 3D file formats, explore our guide Understanding 3D File Formats: A Complete Guide for Designers, Engineers, and 3D Enthusiasts.

Real-World Examples

Case Video 1

From Scale to Detail: 3D Scanning Historic Architecture

In this heritage preservation project, large-scale LiDAR scanning was used to capture the overall layout of a 745 m² traditional courtyard house, while EinScan Libre recorded the fine details of its intricate wooden carvings. Together, the datasets created a comprehensive digital record to support restoration, research, and preservation.

Case video 2

Large-Scale and Fine-Detail 3D Scanning for Surveying and Mapping

This workflow combines large-scale LiDAR scanning with EinScan Libre to capture both expansive environments and intricate features. The integrated approach supports efficient and comprehensive 3D data collection for applications such as surveying, mapping, and construction.