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Updated quick start guide (QSG)
12/06/2020 at 06:22 • 0 comments1. Added the description of the PCB layers in the QSG.
2. Added slides to describe the ability to save the displayed image on the MVM Monitoring Software in raw or bitmap format on the computer, and also to retrieve the saved image using routines developed in MATLAB, Scilab or Python. This is useful if we want to develop some image processing algorithms to the captured image from the MVM.
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Support for TFT LCD Display
11/02/2020 at 09:43 • 0 comments2 Nov 2020:
Added support for 320x240 QVGA LCD display. Please see project details above.
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WiFi link with ESP8266 [Update Nov 2021]
09/22/2020 at 07:08 • 0 commentsThe present version send the image data to a remote computer for viewing the image captured by the module via Bluetooth module or USB-to-Serial converter. Currently I am experimenting with using the popular ESP8266 to broadcast the image data to the remote computer via WiFi, using TCP or UDP protocols. The ESP8266 will functions as a server, with a client software running on the PC.
Nov 2021: Finally have time to re-look into this project. I have create a firmware version that can support ESP8266. This allows MVM V1.5C to stream images to a remote computer via WiFi connectivity. Currently I am using TCP protocol, with ESP8266 configured as a TCP server, while the remote computer works as a TCP client. Updated the codes on GitHub.
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Convolution Neural Network Support
07/04/2020 at 05:42 • 0 comments1 July 2020:
Added a small convolution neural network (CNN) process into the latest source code (Image Processing Algorithm 4). For now the CNN process is used to classify a small region of the image frame in gray scale for identifying obstacles. For details see https://fkeng.blogspot.com/2020/06/implementing-custom-convolutional.html