For many users, the smartphone’s camera is one of the most necessary aspects. It has many uses, from magical overlays of virtual beings to reality.
However, the functionality of your smartphone’s camera is much wider. It represents itself as a visual search engine and selects just about everything you see in the world. It can help you with everything from basic acquaintances to shopping. Isn’t this a good idea for a custom digital project? Then, try to build image recognition app. You can do it yourself or by relying on a team of professionals, like Perpetio.
So, if you don’t want to miss out on another key feature of the well-known smartphone’s camera, keep on reading!
How is the term “object recognition” generally defined?
Well, object recognition is a computer vision approach for determining objects in the picture and even video content. Object recognition is the main result of deep and machine-learning algorithms. When viewing photos or videos, a person can easily recognize people, objects, scenes, and visual details. The top aim is to explain to the computer what is natural for people: to reach a level of knowledge of what the image includes.
Object recognition is an important technology for self-driving cars, allowing them to recognize stop signs or distinguish between a pedestrian and a light pole. Moreover, it is also helpful in various modern applications.
Object recognition and object detection
Object detection and object recognition are equal methods for determining objects. Yet, they differ in their implementation. As for deep learning, the use of object detection methods works not only to recognize an object but also to locate it on the image. This allows you to identify multiple objects and place them on the same image.
How the object recognition works
It is possible to use different approaches for object recognition. Newly, machine and deep learning methods have become wide-spread ways of object recognition difficulty. What’s interesting is that each of these technologies is targeted to define objects in images. Still, they are not similar in their execution.
The article part shows the contrast between machine learning and deep learning for object perception and says how to use both approaches.
The most popular methods of object recognition
Well, even though digital technologies are unstoppable, for now, there are several reliable methods for successful object recognition.
Object recognition using deep learning
Nowadays deep learning models are often applied to provide a mechanized examination of the inherent properties of an object. This helps pinpoint that object effectively.
There are two approaches to object recognition using deep learning:
- Training the model from scratch. If you want to train a deep network from scratch, first try to gather a big tagged dataset. Then, create a network structure. Pay attention that it will be responsible for learning the features and building a model.
- Relying on a pre-trained deep learning model. Do you know what method is used by most deep learning applications? For sure, it is a transfer learning method. In brief, it is an action that includes refinements of a pre-trained model. Furthermore, this approach requires less time. As well, it guarantees quicker and more successful results. You may like it.
Machine learning object recognition
The best-known examples of machine learning methods are usually:
- extracting HOG features using the SVM machine learning model;
- bag-of-words models with varied useful proses, like SURF and MSER;
- is a Viola-Jones algorithm that can be used to recognize various objects, including faces and upper body.
Machine learning process
To recognize objects using a standard machine learning approach, you need to start with a set of images (or videos) and select the appropriate feature in each image. These cool features are attached to a machine learning model, so it can classify them. Afterward, the machine learning model will be able to apply this data to examine and sort new-coming objects.
As you see, this process is very exciting. Do not hesitate to try varied machine learning strategies and feature stock approaches, as they provide useful so-called units to build a nice object recognition model.
Machine learning for object recognition
Machine Learning (ML) is a technology that allows computers to automatically learn and improve without being explicitly programmed. It uses algorithms that learn and improve based on experience. Machine learning is often used to solve problems where complex rules are hard to define. Machine learning can then be used to make informed decisions.
Deep learning for effective object recognition
Deep learning is a technology based on machine learning and is particularly well suited for processing large amounts of data. Thus, deep learning is a field of machine learning. Deep learning uses artificial neural networks to recognize patterns and relationships in data. Networks are divided into different layers, which allows them to solve complex problems. Deep learning is often used to analyze images and videos and extract information from them. Unlike machine learning, where developers often intervene to make adjustments, in deep learning, the algorithms themselves determine the correctness of decisions.
Other object recognition methods
Depending on the task, other, simpler approaches to object recognition may be sufficient:
- Pattern matching. It utilizes a tiny image to find relevant areas in a large image.
- As well, we can’t but mention image segmentation and, of course, blob analysis.
As a general rule, if an object can be recognized using a simple approach such as image segmentation, it is best to start with the simpler approach.
Wrapping it up
Due to advances in image recognition technology, unknown objects in the world around us are no longer a mystery. With these apps, you can identify almost anything, be it a plant, a stone, jewelry, or a coin.
These platforms are based on a network of machine learning algorithms (like the ones you can create with Microsoft Lobe). It is becoming more and more popular in digital products, so you should have a general understanding of it. Or, if you want to get quick and high-quality assistance from experienced specialists, contact Perpetio. They will help you build the best image recognition app. Thank you for your attention!
