Major Project Color detection and tracking with ESP32 Cam and OpenCV.

1. Color Detection &Tracking with ESP32
CAM & OpenCV
Name of the Students:-
SAURABH SINGH(1907042)
AMIT KUMAR(1907006)
SHIVAM(1907046)
SAARTHAK GIRI(1907039)
Major Project
Under the Supervision of :-
PROF. ISRAJ ALI
School of Electronics

2. Overview:-
This project is all about Color Detection & Tracking with ESP32 CAM Module & OpenCV.
We will be detecting any specific colors during live video streaming. Colour detection is
necessary to recognize objects, it is also used as a tool in various image editing and
drawing apps.
Here we have used the ESP32-CAM module, which is a small camera with the ESP32-S
Chip. Besides the OV2640 camera and several GPIOs to connect peripherals,it also
features a microSD card slot that can be useful to store images taken with the camera.

3. Bill of Material:-
S.N COMPONENTS QUANTITY
1. ESP32 CAM Board 1
2. FTDI Module 1
3. USB Cable 1
4. Jumper Wires 10

4. Components:-
The following is the list of Components for building an ESP32 CAM Based Color
Detection System.
ESP32-CAM Board
FTDI Module
USB Cable
Jumper Wires
AI-Thinker ESP32 Camera Module
USB-to-TTL Converter Module
5V Mini-USB Data Cable
Male/Female to Female Connectors
Description

5. ESP32 CAM Module :-
The ESP32 Based Camera Module developed by AI-Thinker.
And the controller is based on a 32-bit CPU with a frequency of up tp 240 MHz. It has built-in
520 KB SRAM with an external 4M PSRAM. It has a combined 802.11b/g/n Wi-Fi +
Bluetooth/BLE SoC module.
It supports image WiFi upload and Embedded Lwip and FreeRTOS. There is an onboard
voltage regulator IC and a PSRAM Chip.
This module has already an antenna attached. But if we want to use an external antenna of
better power and better range, we can connect an antenna to the IPEX connector.
The ESP32-CAM is a very small camera module with the ESP32-S chip. The module has an
OV2640 camera and it also has several GPIOs to connect peripherals.

6. Image of ESP32-CAM :-
Back Side
Front Side

7. OV2460 Camera:-
The most important part of ESP32 CAM is the Camera module.
Camera Module which has a 24 Pin Camera Holder and it has the highest Camera
Resolution up to 1600 X 1200.

8. SD Card Support :-
On the backside, there is an SD Card Holder which supports SD Card up to 4GB.
The SD Card is used for storing images while making image based projects. For learning, we
can use a 4GB SD Card. We can simply slide and insert the SD Card into the SD Card Adapter.

9. ESP32 CAM GPIO Pins :-
There are several GPIOs Pins that have
support like UART, SPI, I2C, PWM, ADC, and
DAC .
3.3V VCC pins as well as a 5V Pin from this
module. There are multiple GND Pins as
well.
The following pins are internally connected to microSD card reader :
GPIO 14: CLK
GPIO 15: CMD
GPIO 2: Data 0
GPIO 4: Data 1 (also connected to the on-board LED)
GPIO 12: Data 2
GPIO 13: Data 3

10. ESP32-CAM FTDI Connection :-
For programming the board, we need any USB-to-TTL Converter Module or an FTDI Module.
There are so many FTDI Module available based on CP2102 or CP2104 Chip or any other chip.
For getting started with ESP32 CAM Module, we make a following connection between FTDI
Module and ESP32 CAM module.
ESP32-CAM FTDI PROGRAMMER
GND
5V
U0R
U0T
GPIO 0
GND
VCC (5V)
T
X
RX
GND

11. Connect the 5V and GND Pin of ESP32 to 5V and GND of FTDI Module. Similarly,
connect the Rx to UOT and Tx to UOR Pin .And the most important thing, you need
to short the IO0 and GND Pin together.

12. Code:-

13. Result:-

14. Conclusion:-
• Color detection technology has come a long way and has a long way to go. When we
see selfdrive cars running on roads by themselves following the traffic rules. Today,
the machines are ready to for it. Tesla is a front runner in this technology. However,
next-generation color detection programs will have more upgradations. The apps in
smart environments - where computers and equipment are similar to assistant
assistants.
• To achieve this goal computers must be able to reliably identify nearby things and
their basic properties like size shape and color in a manner that is naturally consistent
within the normal human pattern. They do not require special interactions and
should be in line with people's understanding of when recognition goes. This suggests
that future intelligent environments should use the same methods as humans, and
have the same limitations. These goals are now achievable.

15. Thankyou