1. Multispectral Camera Simon Belkin, Audrey Finken, Grant George, Matthew Walczak Faculty Advisor: Prof. Mario Parente Department of Electrical and Computer Engineering ECE 415/ECE 416 – SENIOR DESIGN PROJECT 2013 College of Engineering - University of Massachusetts Amherst SDP13 Abstract Block Diagram System Overview Results Specifications Acknowledgements Team Logo Multi-spectral cameras capture images through special optical filters, essentially band-pass filters, which allow only a certain range of wavelengths to pass through while blocking out the rest. The multi-spectral camera system will be operated by a Raspberry-Pi brand microcontroller system. This system will position an individual filter in front of a monochromatic camera and an image will be captured, processed, and displayed to the operator We would like to thank: Seahorse Bioscience for donating the filter wheel used in this project. Akshaya Shanmugam for her help in Spectrometer Testing  System electronically commands and controls the filter wheel assembly and monochrome camera  Differentiate between various rocks based on the spectrum provided  Pixels of images taken at various filters alignments  Project budget is set at $500  Filter wheel thickness required optical engineering to determine required focal lengths The primary goal of the SDP13 Multi-Spectral Camera System is to develop an affordable multi- spectral imagery system that will have the ability to be installed onto a Mars Rover type of vehicle and perform imagery analysis at close to medium distances, (.3-10m). A secondary goal is to create a very useful, and relatively affordable multi- spectral imagery system that enables amateur scientists to view and learn about their surroundings in an affordable and non- complicated way No Filter425nm 436nm450nm 860nm 510nm 750nm 990nm

2. Cost Accounting Raspberry Pi Getting Images via Image Registration Development (R&D Costs) Production Cost ItemUnit CostItemUnit Cost Filter Wheel$0.00Filter Wheel$350.00 Raspberry Pi$0.00Raspberry$35.00 Mightex USB Camera$219.00Mightex USB Camera$127.02 Pentax Lens$99.95Pentax Lens$57.97 Bi-Convex Lens$4.00Bi-Convex Lens$2.32 Adaptor - C-Mount to SM1$19.75 Adaptor - C-Mount to SM1$11.46 Lens Tube 0.5"$12.59Lens Tube 0.5"$7.30 Lens Tube 3.0"$25.75Lens Tube 3.0"$14.94 Stepper Motor Driver$14.95Stepper Motor Driver$8.67 Adaptor - C-Mount M/M$25.00 Adaptor - C-Mount M/M$14.50 Filter 425nm Filter$0.00Filter 425nm Filter$57.42 Filter 436nm Filter$37.00Filter 436nm Filter$20.00 Filter 670nm Filter$35.00Filter 670nm Filter$20.30 Filter 750nm Filter$99.00Filter 750nm Filter$57.42 Filter 860nm Filter$99.00Filter 860nm Filter$57.42 Filter 990nm Filter$99.00Filter 990nm Filter$57.42 Total Part Cost$785.99 Total Part Cost$899.16 Optics and Ray Tracing Filter Selection Above are the important wavelengths that differentiate the rocks based on those values Extension tubes added to facilitate a greater focal length. Thin lens equation, 1/d i = 1/f – 1/d o, determines the distance to the object, d o, and to the image, d i. Image Registration is the process of estimating an optimal transformation between two images. We transformed a picture taken with filters based on a reference image taken without filters. The Software was done in python to work on the pi. Geometric calibration was done in Matlab to remove geometric distortions caused by various filters. The images above were taken from Matlab while performing camera calibration. It shows the distortion model of images from filters and the settings of the camera at various filters