SICK is one of the world’s leading solutions providers for sensor-based applications in the industrial sector. Founded in 1946 by Dr.-Ing. e. h. Erwin Sick, the company with headquarters in Waldkirch, Breisgau near Freiburg ranks among the technological market leaders. With more than 50 subsidiaries and equity investments as well as numerous agencies, SICK maintains a presence around the globe. SICK has more than 12,000 employees worldwide and generated a group revenue of around EUR 2.3 billion in the 2023 fiscal year.

SICK is one of the world’s leading solutions providers for sensor-based applications in the industrial sector. Founded in 1946 by Dr.-Ing. e. h. Erwin Sick, the company with headquarters in Waldkirch, Breisgau near Freiburg ranks among the technological market leaders. With more than 50 subsidiaries and equity investments as well as numerous agencies, SICK maintains a presence around the globe. SICK has more than 12,000 employees worldwide and generated a group revenue of around EUR 2.3 billion in the 2023 fiscal year.

Thesis: Synthetic images for machine vision and image processing*

Thesis: Synthetic images for machine vision and image processing*

SICK AG
SICK AG

Waldkirch (bei Freiburg), DE, 79183

Waldkirch (bei Freiburg), DE, 79183

Full-time
Full-time

Winter semester 2024/25 – limited to 3-6 months

 

Synthetic images for machine vision and image processing:

In the past decades, camera systems with increasingly sophisticated capabilities have become ubiquitous. Ranging from cameras embedded in our smartphones to camera arrays in self-driving cars and camera systems controlling industrial manufacturing process, these systems are revolutionizing industries and our everyday lives. At the heart of all these imaging systems lies the image acquisition process with the aim to achieve a “good” input image. Therefore, machine vision engineers often spend a lot of time and go through some empirical best practices to try and evaluate different geometrical and optical configurations of the imaging system. To speed up this tedious task, realistic synthetic images allow to evaluate, analyze, and optimize imaging setups without employing physical parts and sensors. To this end sensor-realistic synthetic images are needed, including noise and defects.

 

The goal in this thesis will be to setup a simulation to produce realistic synthetic images, starting with a virtual environment, simulating the imaging process, and then processing the images computationally. 

 

YOUR TASKS:

  • You compare different simulation tool chains
  • You set up a tool chain to generate realistic synthetic images
  • You evaluate different detection task based on synthetic images

 

YOUR PROFILE: 

  • You are studying Computer Science, Computer Vision, Machine Learning or a related field
  • Basic knowledge in optics and physics
  • Programming skills in e.g. Python, Matlab 
  • You are a team player 
  • Your independent and creative working style rounds off your profile

 

YOUR APPLICATION:

  • We are looking forward to your online application
  • Sarah Disch
  • Job-ID 35861 
  • All applications will be treated confidentially

 

*At SICK, we see people, not gender. 

We put great emphasis on diversity, reject discrimination and do not think in categories such as gender, ethnicity, religion, disability, age or sexual identity.

Stichworte: Student, Studentin, Studierende, Masterstudent, Bachelorstudent, Masterand, Bachelorand, Masterstudentin, Bachelorstudentin, Masterandin, Bachelorandin, Master, Bachelor, studienbegleitend, Studi, Studium, Bachelorstudierende, Masterstudierende, Praktikant, Praktikantin, Pflichtpraktikant, Pflichtpraktikantin, Praktika, Praktikum, Pflichtpraktikum, Internship, Intern, Praxissemester, Pflicht, Prakti, freiwillig, Praxis, Semesterpraktikum, Thesis, Masterarbeit, Bachelorarbeit 

Winter semester 2024/25 – limited to 3-6 months

 

Synthetic images for machine vision and image processing:

In the past decades, camera systems with increasingly sophisticated capabilities have become ubiquitous. Ranging from cameras embedded in our smartphones to camera arrays in self-driving cars and camera systems controlling industrial manufacturing process, these systems are revolutionizing industries and our everyday lives. At the heart of all these imaging systems lies the image acquisition process with the aim to achieve a “good” input image. Therefore, machine vision engineers often spend a lot of time and go through some empirical best practices to try and evaluate different geometrical and optical configurations of the imaging system. To speed up this tedious task, realistic synthetic images allow to evaluate, analyze, and optimize imaging setups without employing physical parts and sensors. To this end sensor-realistic synthetic images are needed, including noise and defects.

 

The goal in this thesis will be to setup a simulation to produce realistic synthetic images, starting with a virtual environment, simulating the imaging process, and then processing the images computationally. 

 

YOUR TASKS:

  • You compare different simulation tool chains
  • You set up a tool chain to generate realistic synthetic images
  • You evaluate different detection task based on synthetic images

 

YOUR PROFILE: 

  • You are studying Computer Science, Computer Vision, Machine Learning or a related field
  • Basic knowledge in optics and physics
  • Programming skills in e.g. Python, Matlab 
  • You are a team player 
  • Your independent and creative working style rounds off your profile

 

YOUR APPLICATION:

  • We are looking forward to your online application
  • Sarah Disch
  • Job-ID 35861 
  • All applications will be treated confidentially

 

*At SICK, we see people, not gender. 

We put great emphasis on diversity, reject discrimination and do not think in categories such as gender, ethnicity, religion, disability, age or sexual identity.

Stichworte: Student, Studentin, Studierende, Masterstudent, Bachelorstudent, Masterand, Bachelorand, Masterstudentin, Bachelorstudentin, Masterandin, Bachelorandin, Master, Bachelor, studienbegleitend, Studi, Studium, Bachelorstudierende, Masterstudierende, Praktikant, Praktikantin, Pflichtpraktikant, Pflichtpraktikantin, Praktika, Praktikum, Pflichtpraktikum, Internship, Intern, Praxissemester, Pflicht, Prakti, freiwillig, Praxis, Semesterpraktikum, Thesis, Masterarbeit, Bachelorarbeit 

WHAT YOU CAN LOOK FORWARD TO:

Attractive Remuneration: Internships and theses are attractively remunerated at SICK. 
  
Mobile Work: Students can work remotely as far as their tasks permit. 
  
Flexible Working Hours: The weekly working time is 35 hours with the possibility of compensating overtime with time off. 
  
Subsidised Regional Meals and Free Drinks: Students receive an additional 50% discount in our company restaurants. 
  
Welcome Event and Networking: ‘Welcome @ SICK’ and regular networking opportunities to meet other students. 
  
Training: Wide range of trainings via the Sensor Intelligence Academy. 
  
Support in Finding Accommodation: SICK supports students in their search for accommodation at the Waldkirch and Hamburg locations. 
  
Wide Range of Sports and Hansefit: For an attractive monthly fee, you can use over 8,500 different fitness and leisure facilities throughout Germany. 
 

Discover All Benefits

WHAT YOU CAN LOOK FORWARD TO:

  • Attractive Remuneration
  • Mobile Work
  • Flexible Working Hours
  • Subsidised Food & Free Drinks
  • Welcome Event & Networking
  • Training & Development
  • Support in Finding Accommodation


Discover All Benefits