Type dienstverband:
Internship and graduation project
Den Haag
Uren per week:
Fulltime – 40

Internship | Computer vision for highway inspection

About this position

The Intelligent Imaging department at TNO works on a large variety of computer vision solutions in the field of inspection. One of these projects is the automated inspection of the Dutch highways, where our algorithms are used to monitor the state of the highways and to indicate when sections of highway need to be repaired or replaced. Every year, a high-resolution 3D scan is recorded of all Dutch highways (approximately 15.000 km worth of highway lanes). Our task is to extract as much information as possible from this extremely large amount of data. Currently, different categories of road damage are already automatically detected such as cracks or absolute wear. During your project, you will research new computer vision solutions that will help to keep the Dutch highways well maintained and safe.

What will be your role?

There are many possibilities for a project in the field of road inspection. A number of research directions are listed below to give you a better understanding on what your internship/graduation project could look like. The exact topic of your project will be determined based on your interests and background, so please mention these in your application.

Possible projects:

  • Road segmentation for lane width estimation: The vehicles used to obtain the 3D profile of the road drive across all highway lanes. However, the hard shoulders are not measured. For this project, we are interested in the width of each line, including the hard shoulder by using dashcam footage of the vehicles. The idea is that by automatic segmentation, an accurate estimate of the lane width can be made.
  • Classification of crack like structures: Across the whole Dutch highway system are a large variety of different possible damage types. We are interested in classifying each piece of damage as carefully as possible. Currently, it is challenging to accurately classify different crack-like structures that have similar visual features, such as actual cracks, local repairs, pavement joints, road markings, or long stretches of general wear. In this project, you will investigate (deep learning) solutions to perform this automatic classification.
  • Pavement type classification: Not all asphalt is the same, there are actually several different types of asphalt used to pave the Dutch highways. It is difficult to accurately estimate the amount of general wear accurately without knowing the exact asphalt type. A rough porous type of asphalt might look damaged if you would think it was a fine, dense piece of asphalt. During this project, you will create an algorithm to classify different types of asphalt based, or even estimate the approximate stone-size distribution within the asphalt.

You will perform this assignment in the Intelligent Imaging department. TNO’s Intelligent Imaging group is specialized in image processing, image enhancement, image analysis, visual pattern recognition, artificial intelligence and deep learning. This young, passionate, creative and committed group (50 people) works with partners on technological breakthroughs for innovations in important societal and economic themes, developing knowledge in various research areas including both AI (e.g. learning with less data or hybrid AI) as well as crucial non-AI knowledge, real-time algorithms, edge processing and information fusion.

The project duration is flexible, but preferably within the range of 6 to 12 months. Please mention in your application whether you are looking for an internship or a graduation project, the preferred length of your project and your desired starting date. When doing an internship/graduation project at TNO you will receive an appropriate internship fee.

Keywords to describe this project include: Artificial intelligence, Computer Vision, Image Classification, Detection, Segmentation, Deep Learning, Machine Learning , Road Inspection, Highway Pavement Inspection.

What we expect from you

You are in the final stages of your master’s degree in artificial intelligence, computer science, physics, mathematics, electrical engineering, or a similar degree, you have experience in programming (e.g. Python or Matlab) and preferably have some prior experience with computer vision and/or image processing algorithms.

What you'll get in return

You want to work on the precursor of your career; a work placement gives you an opportunity to take a good look at your prospective future employer. TNO goes a step further. It’s not just looking that interests us; you and your knowledge are essential to our innovation. That’s why we attach a great deal of value to your personal and professional development. You will, of course, be properly supervised during your work placement and be given the scope for you to get the best out of yourself. Naturally, we provide suitable work placement compensation.

TNO as an employer

At TNO, we innovate for a healthier, safer and more sustainable life. And for a strong economy. Since 1932, we have been making knowledge and technology available for the common good. We find each other in wonder and ingenuity. We are driven to push boundaries. There is all the space and support for your talent and ambition. You work with people who will challenge you: who inspire you and want to learn from you. Our state-of-the-art facilities are there to realize your vision. What you do at TNO matters: impact makes the difference. Because with every innovation you contribute to tomorrow’s world. Read more about TNO as an employer.

At TNO we encourage an inclusive work environment, where you can be yourself. Whatever your story and whatever unique qualities you bring to the table. It is by combining our unique strengths and perspectives that we are able to develop innovations that make a real difference in society. Want to know more? Read what steps we are taking in the area of diversity and inclusion.

The selection process

After the first CV selection, the application process will be conducted by the concerning department. TNO will provide a suitable internship agreement. If you have any questions about this vacancy, you can contact the contact person mentioned below.

Students must reside in the Netherlands before the start and also throughout the internship or graduation project at TNO.

Has this job opening sparked your interest?

Then we’d like to hear from you! Please contact us for more information about the job or the selection process. To apply, please upload your CV and covering letter using the ‘apply now’ button.