Top 5 Computer vision Project ideas in 2022

4 min readOct 11, 2022

Top 5 Computer vision Project ideas in 2022

1.Pedestrian detection
Developing a computer vision project to detect pedestrians using an object detection model is one of the quickest and easiest projects to finish using computer vision.

Detection of pedestrians in a shopping centre using V7

For the purpose of training and validating your model, all you want is a pertinent dataset consisting of high-quality photos and a data training platform. You may check out V7 or utilise one of the free programmes that are available for image annotation.

Pedestrian detectors are utilised frequently in the automotive sector for the purpose of ensuring the safety of pedestrian traffic, in addition to their applications in human-robot interactions and intelligent video systems.

Take into consideration the following datasets as a starting point:

The Pedestrian Dataset from Caltech

Database for Pedestrian Detection Developed by Penn and Fudan

Dataset for the Detection of Pedestrians (Kaggle)

2.The recognition of hand gestures
The recognition of hand movements is a computer vision job that is considered to be of a more sophisticated level. In order to recognise hand gestures, you must first isolate the hand region from the backdrop, and then segment the fingers of the hand.

You can use OpenCV if you want to maintain the simplicity of your model, or you can make use of the keypoint skeleton and custom polygons tools that are available in V7 to make labelling both quicker and more precise.

Following training, you will be able to validate your model by utilising a camera. Virtual reality games and sign languages both have applications for hand gesture models.

To get you started, take a look at the following datasets:

Signs with the digits 0 through 5 made with the hands

Database for the Recognition of Hand Gestures

Multi-Modal Hand Gesture Dataset

3.License plate recognition
One further possibility for a computer vision project that makes use of OCR is the creation of a licence plate reader.

Nevertheless, there are two difficulties associated with this project: the collecting of data and the variations in the formats of licence plates that occur depending on the place or country.

Unless you train your model with a substantial amount of data, it is possible that it will not be accurate (if you manage to obtain it).

Note that licence plate numbers are considered private information; therefore, while developing your models, be sure to only use datasets that are accessible to the general public.

The V& Text Scanner was used for licence plate identification on a white Vitare.

You may construct a straightforward automatic licence plate recognition system by making advantage of fundamental image processing methods and constructing it with OpenCV and Python.

On the other hand, more sophisticated systems make use of object detectors such as YOLO or Fast C-RNN.

There are a variety of applications for automatic licence plate recognition, including access control, parking, smart cities, and the collection of automatic tolls.

The following are some datasets that you may want to take into consideration:

Detection of Vehicle License Plates

UCSD Car Dataset

License Plates on Motor Vehicles

4.The Different Types of Iris Flowers
Another experiment based on computer vision, this time using the Iris Flowers Classification Dataset, which is one of the most widely used and therefore easily accessible datasets for pattern recognition.

It is composed of three classes, each with fifty occurrences, and each class relates to a distinct variety of iris plant.

Because you will be training your model to identify the species of a new iris bloom, this project is ideal for those who are just starting out and want to gain some practical experience with image classification.

5.Colors detection
The next tool is a straightforward colour analyzer, which may be put to use for a diverse range of visual activities.

Building a colour recognizer can be used for a variety of projects, including developing a green screen app (which replaces the green background with a custom video or background) as well as a straightforward photo editing programme. This is an excellent project for beginners interested in computer vision.

The following are some interesting datasets that you may want to consider using for your project:

Google-512 dataset

Lego colours

Passport colours