Embedded Vision · Motion Control · Linux

Embedded Vision & Motion-Control Platform

Automated Raspberry Pi 5 microscopy platform combining imaging, motorized motion, autofocus, remote operation, and computer-vision processing.

Raspberry Pi 5PythonLinuxIMX477OpenCVYOLOSSH/RTSP

Overview

This page is the working case-study shell. We’ll replace this text with the exact problem, requirements, constraints, and scope from your project.

This system is being developed to automate the identification and analysis of abnormal white blood cells in microscope imagery. The target cell types include granulocytes such as neutrophils, eosinophils, and basophils, as well as agranulocytes including lymphocytes and monocytes. The platform combines automated microscopy, motorized stage control, image acquisition, autofocus, and computer-vision-based cell detection to reduce the amount of manual scanning required during slide analysis. The long-term objective is to create a system capable of locating candidate abnormal cells and presenting them for further review.

System Architecture

Remote PC → Tailscale / SSH / RTSP → Raspberry Pi 5\n ├─ IMX477 Camera → Image Acquisition → OpenCV / YOLO\n └─ Motion Control → Stepper Drivers → Motorized Stage

My Contribution

Integrated camera, Linux host, motion-control hardware, and computer-vision software.
Implemented autofocus, image acquisition, trajectory planning, and remote system operation.
Configured and tested remote access and streaming workflows.

Photos & Evidence

YOLO white blood cell detection result — YOLO-based white blood cell detection on microscope imagery.

Integration & Debugging

We’ll document 2–3 real faults you diagnosed. Good candidates include camera/streaming failures, motion-control communication problems, remote-access issues, and Linux/display/process conflicts. Throughout the process of building this design i encountered a few noteworthy problems which I will list here, the first being the autofocus inconsistancy / return-to-best error. Due to the physical mechanics of the belt and pully system of the stepper gear box and the gearbox istelf having backlash, due to the small spacing between the gears in the gearbox and the belt and pully system, the autofocus would sometimes return to a position that was not the best focus. This was solved by finding a tuned backlash compensation value for the Z stage, so when the system would return it would backstep the correct amount to ensure the best focus was achieved.

Results & Validation

Add measured or observable outcomes here: autofocus behavior, motion repeatability, streaming performance, detection output, or other system-level validation.