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Computer Vision Applications: How Your Business Can Leverage It


Today we have the opportunity to observe the breakthroughs in the field of artificial intelligence. The earliest studies of this technology date back to the middle of the 20th century.


Of course, those studies were quite primitive, but they’ve made a massive contribution to today’s reality. Things that were shown in science fiction films 30 years ago, today do not seem to be so fantastic.

History of AI:

Humanity is constantly tracking the stages of technology development in areas related to artificial intelligence.


Today we will focus on one of these areas, namely, computer vision, and consider in detail what technologies already exist and how they’re helping us in everyday life.


Table of Content:

  • The Most Popular Areas of Computer Vision Application Usage
    • Retail
    • Automotive
    • Healthcare
    • Agriculture
    • Financial Services
    • Industry
    • Security
  • How to Develop Computer Vision Applications and Apply It in Your Business
  • Challenges of Applying Computer Vision

In simple words, computer vision is a technology that makes devices see. From a technical point of view, these are systems and algorithms for automatic capturing and analyzing images and extracting the necessary information from them.

To date, this area of research is still relatively young, but we can already see the result.let’s take a closer look at the main areas of computer vision applications and find out what the experts have already managed to achieve.

The Most Popular Areas of Computer Vision Application Usage

The computer vision technology has already managed to take its place in some areas of business and in our lives. Moreover, most people use such technologies every day, and some of them are still not aware of this.

Retail

One of the existing solutions which is worth to be mentioned is the AmazonGo store. To purchase in this store, visitors do not need to stand in line to pay for goods.


The presented technology is called “Just Walk Out” and works in the following way. First, each client should preinstall the mobile application. Inside the store, under the ceiling, above the food islands and on the shelves, there are video cameras constantly analyzing the information about the products taken and about the one who makes it.


Thus, a virtual shopping list is automatically generated in the customer’s mobile application, in real time. If the person returns the good back to the shelf, the system recognizes this action and delete it from the list. Once buyers have taken everything needed, they can just leave the store, and the price to be paid for goods will be automatically charged from the customer’s personal Amazon account.


Easy, isn’t it?


However, that’s not all. There is a lot of other technologies that allow shoppers to get a more positive experience. Here are some examples of computer vision applications:

  • Echo Look. This voice-activated gadget takes photos of the user dressed in different outfits and then gives recommendations on which one is better.
  • ScanItAll (by ShopLift) - video surveillance system aimed at avoiding erroneous or intentional skipping scans of goods in stores. The algorithm determines the specific behavior of the cashier when he or she tries to close the barcode, place one product over another, etc.
  • Some companies are considering installing video cameras in shopping carts. The algorithm should determine the contents of the cart and make recommendations on additional products that the customer may also need.
  • Several marketing campaigns also involve the use of computer vision technology. For example, by scanning a visitor, the camera determines gender and age, and depending on these data, provides the customer with targeted advertising on the interactive stands.
  • And what about assessing the staff performance with the help of technology that helps to track customer satisfaction after being served?

Automotive

Over the past five years, computer vision application specialists have achieved unprecedented results. The most discussed topic in this area is, perhaps, cars driving without human help.


Specialists try to create computer vision algorithms and applications for perfect car autopilot, which can accurately move vehicles along busy streets and under any weather condition.

Healthcare

One of the key methods of using computer vision applications in healthcare is the analysis of X-ray ultrasound and tomography pictures of the patients. Some of the most exciting tasks that modern researches set for these applications are:

  • Creating algorithms that can automatically detect circulating tumor cells.
  • Segment the brain MRI images into anatomical structures.
  • Analyze ultrasound images to quickly and accurately diagnose dangerous diseases.

Agriculture

We also should not underestimate the benefits that computer vision technology can bring to agriculture.


One of the latest technologies developed in this area was the computer vision-equipped drone connected to a whole system of sensors, networks, processors and analytics tools.


Developers claim that this device helps farmers to monitor the condition of the soil and crops, measure the amount of fertilizer and distinguish the affected plants. Upon receipt of such data, farmers will be able to urgently take measures to improve the condition of crops, thereby increasing yields and, consequently, profits.

Financial services

Good news for those who want to open a bank account, but lacks time to come to the bank outlet. Today, such major players in the banking sector like BBVA, Number26, and others, are introducing systems that help to attract new customers massively. Most of the banking transactions and operations can be done remotely. Potential clients only need to take photos of their documents, and the bank application will check the authenticity of the images. In such a way, the client receives the feedback almost immediately.

Industry

To support and optimize the production process, computer vision specialists look for ways to control quality, detect product defects, automate the management of the whole manufacture complexes and other operations. Some of these computer vision industry applications are currently used in different industries around the world and help reduce the level of human intervention.

Security

Most of the methods that law enforcement agencies use to identify and find criminals (fingerprints, facial recognition tools, etc.) exist thanks to developing computer vision technologies. 


Besides, modern video surveillance systems are able not only to trace the movement but also to understand who has got into the protected area (adult, child or animal). Having analyzed the situation, the system can raise the alarm if necessary.


Today, such means are often engaged not only in the production but also in residential buildings and apartments by people who want to protect their property from unwanted guests. 


All these and other achievements that will appear in the nearest future, promise to change both, businesses and people’s lives positively. However, it is worth noting that the majority of smart technologies and artificial intelligence studies breakthroughs are still at the stage of active testing, constant improvements and are still not ready to enter the mass market.

Google, Apple, Facebook, and other world-famous companies make a significant contribution to the computer vision app development and constantly launch new startups.

From all the above, we can conclude: soon, very soon, we will observe the real innovations in the studies of artificial intelligence in general and computer vision in particular.

If you do not want to stand aside watching the changes taking place, now it is time to launch your own project and implement your ideas. To do this, first, it is worth understanding what steps the process of creating computer vision applications involves and what problems you may face.


This is what we will talk about next.

How to Develop Computer Vision Application and Apply It to Your Business

Considering the systems themselves and their goals may significantly differ from time to time, the process of creating each specific technology also differs. Therefore, it is quite complicated to clearly define all the steps and stages of work from the very beginning to the receipt of the finished product until the initial data and specific requirements are received from the client.


However, our team has defined the major milestones and follows it when prototyping computer vision technologies for our clients.

  • Obtaining the baseline data from the customer, in-depth study of the project subject area and formation of the detailed technical task. 
    We study the problem in detail and form the idea about the possible ways of its implementation. This step gives us the opportunity to evaluate the existing salvations in the field, assess their quality, and offer the client our own strategies.
  • Determine the technologies, libraries, and algorithms to be used. 
    The complexity of this stage lies in the abundance of these algorithms and technologies. For example, today there more than ten image processing methods:
    • Pixel counter;
    • Selection of related areas;
    • Binarization;
    • Barcode reading;
    • Optical character recognition;
    • Measuring the size of objects;
    • Pattern matching, etc.
      Our task is to determine the optimal method(s), applying which our application will be able to perform the required tasks adequately.
  • Deciding on the equipment used.
    The standard machine vision system consists of at least one camera, a backlight, specialized software and an algorithm for the data obtaining and analyzing. Technical specification of the equipment is selected individually for each project.
    • The camera’s sensitive element matrix converts the image to a digital value. The quality of the camera matrix and its resolution largely determines the range of tasks implemented by the system.
    • The properly selected lens helps to avoid problems with the focus.
    • Different types of lighting can expand or narrow the scope of functions the system will be eligible to perform in the future.

Prototyping the system for obtaining data from video cameras or streaming video.
At this stage, we determine the location of each part of our computer vision system. One of the typical examples:

  • Prototyping an object recognition network.
    Based on the selected algorithm, we determine the sequence of the resulting image transformations, create a working neural network and develop the necessary software for the system, namely decide on how does the computer vision work. For example, the object recognition network prototype used in the manufacture of industrial equipment will perform the actions in the following sequence:

  • Product manufacturing.
    After the computer vision software development, we combine the prototypes obtained and create a single operating computer vision system. We thoroughly test it and refine it if necessary. After that, the client receives the product ready for use and guaranteed performance of the tasks.

Challenges of Applying Computer Vision

Even though both, global companies and freelance specialists, are currently studying and building machine vision systems, we still do not often face these technologies in our everyday life. For example, there are many ideas for optimizing production processes, controlling product quality, automating researches, etc. however, why are these ideas still so far in development?


 There are several major problems, which often interfere with the implementation of innovative computer vision systems.

  • Modern electronic components for building computer vision systems do not provide the appropriate quality of data collection.
  • The performance of most existing technologies is still far from the ideal, which we strive to reach. To recognize a specific object, the computer must first be taught. This action must be carried out each time anew when the new object is added to the database. It is called machine learning, and it can take too much time to create a decent database for an individual project.
  • It is hard to assemble a team of deep learning specialists with practical work experience, ready to start implementing complex tasks right away. The problem is that in practice, there are few companies ready to hire an employee to train him first, losing valuable time. As a result, we have a shortage of qualified and an abundance of theoretical specialists.

We believe that all these are rather not problems, but temporary inconveniences, which we will soon be able to forget. The experience gained has shown that while working on any similar project, we may anytime face unexpected interferences. For us, this becomes a challenge and a reason for further development and expansion of our skills. 

By overcoming such challenges, we gain invaluable experience helping us to find and implement unique solutions for our clients.

Work with UDTech On Your Computer Vision Project

Do you have an idea, but do not have enough knowledge or experience to implement it? Or maybe, you need help in finding a solution to automate certain stages of production or turnover?


In this case, the UDTech team is ready to help in the implementation of projects and ideas of any complexity.


For more information about the ways, we can help you, write a few words about your project via the “Contact Us” form.