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Selecting the Right Camera for the NVIDIA Jetson and Other Embedded Systems

The camera module is the most integral part of an AI-based embedded system. With so many camera module choices on the market, the selection process may seem…

The camera module is the most integral part of an AI-based embedded system. With so many camera module choices on the market, the selection process may seem overwhelming. This post breaks down the process to help make the right selection for an embedded application, including the NVIDIA Jetson.

Camera selection considerations

Camera module selection involves consideration of three key aspects: sensor, interface (connector), and optics. 

Sensor 

The two main types of electronic image sensors are the charge-coupled device (CCD) and the active-pixel sensor (CMOS). For a CCD sensor, pixel values can only be read on a per-row basis. Each row of pixels is shifted, one by one, into a readout register. For a CMOS sensor, each pixel can be read individually and in parallel. 

CMOS is less expensive and consumes less energy without sacrificing image quality, in most cases. It can also achieve higher frame rates due to the parallel readout of pixel values. However, there are some specific scenarios in which CCD sensors still prevail—for example, when long exposure is necessary and very low-noise images are required, such as in astronomy. 

Electronic shutter 

There are two options for the electronic shutter: global or rolling. A global shutter exposes each pixel to incoming light at the same time. A rolling shutter exposes the pixel rows in a certain order (top to bottom, for example) and can cause distortion (Figure 1).

Two images of a helicopter showing distortion of moving blades caused by rolling shutter.
Figure 1. Distortion of rotor blades caused by rolling shutter

The global shutter is not impacted by motion blur and distortion due to object movement. It is much easier to sync multiple cameras with a global shutter because there is a single point in time when exposure starts. However, sensors with a global shutter are much more expensive than those with a rolling shutter. 

Color or monochrome 

In most cases, a monochrome image sensor is sufficient for typical machine vision tasks like fault detection, presence monitoring, and recording measurements.

With a monochrome sensor, each pixel is usually described by eight bits. With a color sensor, each pixel has eight bits for the red channel, eight bits for the green channel, and eight bits for the blue channel. The color sensor requires processing three times the amount of data, resulting in a higher processing time and, consequently, a slower frame rate.  

Dynamic range 

Dynamic range is the ratio between the maximum and minimum signal that is acquired by the sensor. At the upper limit, pixels appear white for higher values of intensity (saturation), while pixels appear black at the lower limit and below. An HDR of at least 80db is needed for indoor application and up to 140db is needed for outdoor application. 

Resolution 

Resolution is a sensor’s ability to reproduce object details. It can be influenced by factors such as the type of lighting used, the sensor pixel size, and the capabilities of the optics. The smaller the object detail, the higher the required resolution. 

Pixel resolution translates to how many millimeters each pixel is equal to on the image. The higher the resolution, the sharper your image will be. The camera or sensor’s resolution should enable coverage of a feature’s area of at least two pixels. 

CMOS sensors with high resolutions tend to have low frame rates. While a sensor may achieve the resolution you need, it will not capture the quality images you need without achieving enough frames per second. It is important to evaluate the speed of the sensor. 

A general rule of thumb to determine the resolution needed for the use case is shown below and in Figure 2.  The multiplier (2) represents the typical desire to have a minimum two pixels on an object in order to successfully detect it.

Resolution = 2times frac{Field  of  View (FOV)}{Size  of  feature  of  interest}

Diagram showing the representation of a person and the working distance from an object as an example of minimum object feature size of interest in the field of view.
Figure 2. Sensor resolution required is determined by lens field of view and feature of interest size

For example, suppose you have an image of an injury around the eye of a boxer. 

Based on the calculation, 1000 x 1000, a one-megapixel camera should be sufficient to detect the eye using a CV or AI algorithm. 

Note that a sensor is made up of multiple rows of pixels. These pixels are also called photosites. The number of photons collected by a pixel is directly proportional to the size of the pixel. Selecting a larger pixel may seem tempting but may not be the optimal choice in all the cases. 

Small pixel Sensitive to noise (-) Higher spatial resolution for same sensor size (+) Large pixel Less sensitive to noise (+) Less spatial resolution for same sensor size (-) Table 1.  Pros and cons of small and large pixel size

Back-illuminated sensors maximize the amount of light being captured and converted by each photodiode. In front-illuminated sensors, metal wiring above the photodiodes blocks off some photons, hence reducing the amount of light captured.

On the left, a diagram of a front-illuminated structure with substrate, photodiodes, metal wiring, and microlenses. On the right, a diagram of a back-illuminated structure with metal wiring, photodiodes, and microlenses.
Figure 3. Cross-section of a front-illuminated structure (left) and a back-illuminated structure (right)

Frame rate and shutter speed 

The frame rate refers to the number of frames (or images captured) per second (FPS). The frame rate should be determined based on the number of inspections required per second. This correlates with the shutter speed (or exposure time), which is the time that the camera sensor is exposed to capture the image. 

Theoretically, the maximum frame rate is equal to the inverse of the exposure time. But achievable FPS is lower because of latency introduced by frame readout, sensor resolution, and the data transfer rate of the interface including cabling. 

FPS can be increased by reducing the need for large exposure times by adding additional lighting, binning the pixels. 

CMOS sensors can achieve higher FPS, as the process of reading out each pixel can be done more quickly than with the charge transfer in a CCD sensor’s shift register. 

Interface

There are multiple ways to connect the camera module to an embedded system. Typically, for evaluation purposes, cameras with USB and Ethernet interfaces are used because custom driver development is not needed. 

Other important parameters for interface selection are transmission length, data rate, and operating conditions. Table 2 lists the most popular interfaces. Each option has its pros and cons. 

Features USB 3.2 Ethernet (1 GbE) MIPI CSI-2 GMSL2 FPDLINK III Bandwidth 10Gbps 1Gbps DPHY 2.5 Gbps/lane CPHY 5.71 Gbps/lane 6Gbps 4.2Gbps Cable length supported < 5m Up to 100m 

Source:: NVIDIA

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