Things used in this project
Hardware components
| K230 Vision Module |
×1
| 32/64 GB TF Card (optional) |
×1
| Card Reader (optional) |
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| XH-1.25 to 2.54 Cable |
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| Module Cable (200mm) |
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| Type-C Data Cable (1000mm) |
×1
| U-Shaped Base Bracket |
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| L-Shaped Base Bracket |
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| Damping Hinge |
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| M2 metal spacer x6 + M2*8 screw x6 + M3*6 screws x10+ M2*4 screws x6 |
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| Speaker (120mm) |
×1
| Mini Pan-Tilt Servo Platform (Unassembled) |
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Story
Have you ever imagined building a smart security system for your warehouse or studio that can identify individuals and log vehicle information automatically, all for less than the cost of a mid-range smartphone? Traditional solutions often force a difficult choice between expensive cloud-based AI services with ongoing fees and privacy concerns, and limited, single-function local devices.
Today, we break this deadlock. Using the Hiwonder K230 module—a palm-sized vision module packing 6TOPS of equivalent AI performance—we can implement two critical capabilities locally on the device, simultaneously: OCR text recognition and 3D face mesh analysis. This guide will walk you through building a prototype system that not only "reads" text on IDs or license plates but also "sees" in 3D to determine if it’s looking at a real person or a photograph, creating a high-reliability, high-privacy intelligent security checkpoint at the edge.
Part 1: Why Combine OCR with 3D Face?
Before we start building, it’s crucial to understand why this specific combination of technologies is so powerful. Together, they address the core security challenges of "credential verification" and "biometric spoofing."
OCR gives the machine the ability to read. In a security context, this means it can automatically extract ID numbers, license plate information, or tracking numbers, turning visual data into searchable, verifiable structured data. This replaces error-prone and tedious manual entry and verification.
3D Face Mesh technology, on the other hand, represents an evolution in combating security threats. Traditional 2D facial recognition is easily fooled by high-resolution photos or screen replays. 3D face mesh technology counters this by reconstructing the three-dimensional geometry of a face, allowing it to perceive depth, contour, and subtle motions accurately. This enables the system to request actions like "blink" or "nod, " analyzing the uniqueness of these movements in 3D space to perform liveness detection—effectively determining if a live person is present and raising the bar for identity theft significantly.