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Image Sensors

SONY CMOS Image Sensors Overview - Time of Flight
Sony
CMOSIS
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Sony

Sony has released a back-illuminated, time-of-flight (ToF) 3D image sensor*1 for industrial machineries. Applying Sony's sensing and ranging tecnologies, the compact and high-resolution sensor acquires depth map which can cover both short and long distance.

The compact and innovative sensor acquiring accurate depth map, leads to various fields and applications such as forklift pallet detection, load recognition, fruit-picking equipments and auto-milking robots, etc.

Back-illuminated Time of Flight (ToF) 3D image sensors from SONY
Device Structure
Delivers High-Resolution 3D Images

ToF pixel technology and back-illuminated CMOS image sensor pixel technology from Sony bring high resolution, high accuracy and smaller sensor size to ToF systems. The sensor can be used when high-precision object recognition is required or when space is limited, such as on a robot arm.

* : Distance is color-coded in depth images.

Suppresses Blur of Moving Subjects

Unlike mechanical laser scanning, the ToF system does not use any moving parts. This allows fast frame-by-frame acquisition of 3D depth maps with less blur of moving objects. Even fast-moving objects, such as products on conveyor belts can be targeted for sensing.

Reduces Processing Load

Using ToF sensors, distance information can be obtained by performing simple processing on sensor output. Compared to conventional camera imaging, this makes it easier to build a depth-sensing environment. Even when omnidirectional or multi-angle images are generated from several cameras in real time, sensing can be performed by a system configuration with a low processing load.

Improves Robustness in all Environments

Sony's ToF sensors have the pixel drive processing to subtract external light offset, which can be used under high-illuminant environments such as under bright sunshine. This sensor can be used for both indoors and outdoors, including in extremely dark scenes such as in an unlit warehouse.

Examples of ToF Imaging Applications

Automation and labor-saving innovations are becoming key factors for applications using industrial machineries.
ToF sensors, acquiring accurate depth map is one of these key factors. It meets growing needs in recognition, measurement, automation, and other areas such as in production lines, logistics and smart technology in agriculture and livestock.

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SONY Technology Guide

The value of 3D image sensors

In addition to imaging in X and Y directions, 3D image sensors also acquire the Z-direction information, enabling 3D sensing. 3D sensing opens up the possibility of discerning things that are difficult with conventional 2D images, as in inspection based on volume or shape, or discerning overlapped objects. It is also a promising technology for applications utilizing relative distance information in real time, such as automated control or collision avoidance system.

Features of ToF 3D image sensors

ToF sensors measure the distance by using the time difference until the reflected light is detected by the sensor. The light is typically generated by a laser or a LED. There are two main types of ToF. Direct ToF (dToF) involves a simple, direct measurement of the time until reflection is detected. Indirect ToF (iToF) measures distance by collecting reflected light and discerning the phase shift between emitted and reflected light.

The iToF products such as IMX556/IMX570 are especially effective in high-speed, high-resolution 3D imaging of objects at short and long distances.

Features of Sony's ToF sensors

ToF image sensors detect distance information of each pixel, creating highly accurate depth map. Sony's ToF sensor is combined with a pixel technology which highly accurately detects reflected light and the back-illuminated CMOS image sensor technology with high sensitivity and low-noise performance. The back-illuminated CMOS image sensor technology is also designed for faster processing from advances such as multilayer wiring. Greater efficiency of collecting reflected light and faster processing speed lead higher accuracy of distance measurement.

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