Sujets 6.1 : Smiths group

Introduction

Presentation psr Clement Fang

• Ancien Image 2020

Serge Maitrejean

• Responsable de l'innovation
• Doctorat en physique

Eric Garrido

• Doctorat en physique nucleaire

Groupe Smiths

• Cote en bourse a Londres
• 4 divisions
• Smith detection: scanner et detection
  • Detection de choses illicites ou non-declarees

En france:

• Base a Vitry-sur-Seine
• A peu pres 200 personnes
• IA / traitement d'image…

Les techs au sein de Smith

Global presence

Vehicle, cargo & mobile screening

High energy X-ray imaging

Which target / threat we are looking for ?

SD Paris Partnerships

Epita est cense etre la

Cigarettes detection

Some big seizures made thanks to our iCmore in the news

iCmore Weapons detection

More in-depth

Truck Radioscopy

• Imaging with X-Rays but with a scanning principle

• Pulsed X-ray source: X-Ray pulses (flash) oh three
  $\text{mus}$ every 2 or 3 milliseconds
• One vertical line of detectors/pixels (5 or 20 mm width, 5 mm height): one column of image is recorded for each X-ray pulses
• Truck speed is limited: < displacement of detector width between 2 pulses (typically 5-7 km/h)
• Or resolution is bad (large detectors)

A new tech: Matrix detector

• Multicolumn detector (column)

• Large resolution improvement (Left one line, Right Matrix detector)

But noting or nobody is perfect

• First problem: missing part
  
• Easy to solve by slowing down the speed but…
  
  • Superposition: le meme point se voit 2 fois

The problem of depth at low speed: rearranging data ?

• The way of ordering data is depending on the depth where objects are located.. But we don't know the depth ! It's a stereo effect

Ordering data is depending on the depth

• We have to assume where in depth the object are located, if we are wrong strong artifacts appears

Turning a drawback onto an advantage

• Minimizing the artifacts
  $\iff$ Finding the depth of the objects and providing a optimum high resolution image

Curent status

• Proof of concept has been done using energy minimization technics
• Work on this approach is pursuing
• A comprehensive set of data has been acquired from which the "exact images" can be extracted
• We want to test another approach, neural networks and deep learning are good candidates

The work

• Getting familiarized with the problem (not so easy)
• Getting familiarized with the current method
• Initating Matrix Detector Deep Learning process for:
  • Building the best radioscopic planar images
  • Finding the depth where objects are located