Image recognition is one of the features that we've heard a lot about and are included in most modern hardware and software. This feature has a wide range of applications, the most common in security systems. It enables devices to recognize the identity of a person or object only through his image. Face recognition is the product of image recognition.
So, what does it take to create an application or program that has image recognition? You simply need to program the program using a programming language that supports this feature. Of course, there are some languages that can do the job. Here are the best programming languages for image recognition.
1. Matlab
1. Matlab
Matlab is an independent programming language that has its own framework and IDE that provides you with a more robust workspace. The programming language comes with a wide range of tools that you can use to handle technical programming tasks more easily. Image recognition and facial processing are some of the tasks that can be addressed by Matlab. Some of the tools available in Matlab can perform complex image processing tasks such as cropping, scaling, covering, etc.
There is also a Matlab code dedicated to calling and implementing Face Recognition. This code uses the AT & T database. For this reason, you must download the AT & T database before using this code. Most advanced facial recognition applications are written in Matlab.
2.Python
Currently, Python has been classified as the most common programming language. Its simplicity and versatility are among the reasons why many programmers prefer to use it. Although simple, Python is a language you can rely on to perform complex tasks. It can be used to create and recognize image processing features.
It also features a range of libraries for many functions, including photo recognition. One of the most powerful libraries is the Scikit-Learn Machine Learning Library. Apart from image recognition, libraries can be used to perform smarter functions such as face recognition and motion detection.
It also features a range of libraries for many functions, including photo recognition. One of the most powerful libraries is the Scikit-Learn Machine Learning Library. Apart from image recognition, libraries can be used to perform smarter functions such as face recognition and motion detection.
3. C / C ++ / C #
You can not make a mistake when it comes to the C family of programming languages. They are powerful and can do anything, including creating and identifying image processing functions. The C group provides two programming languages for creating the image processing feature. You can choose to program everything from scratch where you type the code manually. The second option is to use existing libraries designed specifically for these software languages. These libraries include OpenGL, EmguCV, OpenCV and many others. They have the advantage of processing smart images to identify images.
4. Java
Such as C and C ++, we can never underestimate the power of Java programming language. This language is powerful enough to perform complex functions. It can be used to create applications for image processing and image recognition.
As an independent programming language, you can create image processing function from scratch. The advantage of this method is that you have full control over the functions. Instead, there are powerful libraries that can be integrated into Java for the purpose of creating an image recognition feature. OpenCV is one of the Java compatible libraries. You can choose the method that suits you.
OpenCV tool
Open Source Computer Vision is an advanced tool used in real-time processing. It is also a multi-platform tool and can then be integrated into any programming language for the purpose of implementing image recognition functions. It can be integrated with the C, C ++, Java, Python and Android programming languages.
OpenCV comes with unprotected algorithms from patents, which means you can use them without any legal restrictions. It can be used for commercial and academic purposes. Contains a custom face recognition category that you can use to experience photo recognition capabilities without any hassles.
There is also a collection of informative documents that will show you how to implement image recognition. In general, OpenCV is a transition tool for image recognition, regardless of the programming language you use.
OpenCV comes with unprotected algorithms from patents, which means you can use them without any legal restrictions. It can be used for commercial and academic purposes. Contains a custom face recognition category that you can use to experience photo recognition capabilities without any hassles.
There is also a collection of informative documents that will show you how to implement image recognition. In general, OpenCV is a transition tool for image recognition, regardless of the programming language you use.
