Executive Summary
Finding lost animals remains a pressing challenge for pet owners. Now, technology enables pet owners to locate and recognize animals more accurately and quickly. Read more about how modern technologies, including AI and computer vision, help animal recognition.
Introduction
Walking in our neighborhoods or offices daily, we see abandoned animals roaming the streets. While some of these animals are abandoned by owners, most of these are just lost. The crux of the problem isn’t people being heartless and cruel to animals, but it’s the complexity involved in finding lost pets.
Thankfully, recent technological advances, especially computer vision and AI image processing, are making it possible for people to find their lost animals. Facial recognition is one such technology we have used for quite some time. The technology is now making its way to help pet owners find their lost pets. The technology is more intended for developing tools for farmers and ranchers to better monitor, track and find their animals. Farmers are increasingly using AI drones equipped with sensors and image processing tools to track and monitor animals across the farms.
Now, when we talk about finding lost animals, we got a few technologies being practiced. One of the technologies used by pet owners is to instill microchips in their pets for location tracking, but it requires invasive surgery. The microchips cannot be ready without specialized devices, and it’s quite convenient for thieves to extract and remove the microchips.
DNA analysis is another method to find and recognize old pets, but it’s expensive and time-draining. This leaves us with AI-based animal detection solutions that offer a faster, more practical, and more affordable solution to find lost animals. So, let’s see what facial recognition software entails for pets!
Pet Finding through Animal Recognition Software
One of the most efficient and reliable methods is leveraging computer vision technology to perform animal facial recognition. Practically speaking, animal Recognition Software still has various caveats, but it still has a higher accuracy level since three primary steps complete the recognition process, including;
1. Image Capturing
In the first step, animal Recognition Software takes animal pictures through a high-end camera, particularly one with higher resolution. Just to be cautious, certain animal recognition software uses algorithms that work only with specific poses (the poses are predefined). For this reason, the pictures that comply with the criteria are selected.
2. Extraction of Features
The second step is to evaluate the biometric data of the pet for suitability. In addition, pre-processing is applied. As a result, the algorithm will extract the specific features essential for pet recognition.
3. Matching
The pet’s extracted features are mathematically represented and matched with other images. For instance, if you’ve to look for a dog in the database of lost pets, the dog’s unique features are matched with features of other animals in the database.
There are multiple methods of matching, clustering being the most popular. Clustering is completed through different algorithms, including DBSCAN and KNN, which create a picture collection. These pictures have higher proximity to the target picture, and the users can manually select the most suitable picture.
Various probabilistic methods can also be used to represent the final results, known as confidence levels. For instance, the algorithm can determine the cat’s image that’s being checked has 90% confidence with a cat and 10% with a dog.
Animal Recognition Software – Simplifying the Process of Pet Rescue!
Losing pets can be extremely frustrating for pet owners – these incidents are very common. According to research, 1/3rd of home-owned cats and dogs go missing in the US, and 80% of them are never traced back.
For this reason, multiple facial recognition initiatives help owners find their lost pets. The web or mobile apps are designed with an extensive database of millions of animals. In addition, the pet owners can put in their pet’s picture and add different characteristics of the pet.
As a result, the pet facial recognition software scans the provided picture and sees if it corresponds to the animal from the database. You will get a match if the characteristics and picture match the registered animal. In most cases, the match also provides contact information about the person who found the pet.
These applications use advanced facial recognition technology, algorithms, and biometrics. Some apps have more than 100 scan points to deliver accurate results. The majority of these apps have 98% accuracy.
Conclusion
To sum up, the advancement in computer vision and AI technologies have come to the point that we are now increasingly seeing new apps being developed for pet recognition. The good news is that the technology has already been around for quite some time and has matured greatly. We expect to see an increasing number of animal recognition software developed in the coming years. However, there remain caveats in animal recognition technology, but advancements like image analysis have proven up to 98% accurate, which is not only a viable option but incredibly helpful!
