Use a Camera Model to Accelerate Camera System Design

The exciting world of embedded cameras is experiencing rapid growth. Digital-imaging technology is being integrated into a wide range of new products and systems. In particular, embedded cameras are becoming widely adopted in the automotive market, security and surveillance markets, medical market, and industrial systems market. In fact, image sensor sales growth in these markets is predicted to out pace the smartphone and digital camera markets. This is the result of the mass availability of increasingly powerful, low-cost processors and the continued performance enhancement and cost reduction of CMOS image sensors.

Designing an embedded camera can be complex. There are numerous sensor, lens, lighting, and system trade-offs that need to be made to meet the desired application constraints. At Twisthink, we employ “lean” thinking to embedded vision applications by applying mathematical camera models to understand the trades and accelerate the camera design for our clients.

Camera models are especially valuable in the early stages of the product design because it allows designers to:

• Quickly understand the class of camera required by an application
• Easily make appropriate trade-offs with visual relationships between camera design parameters
• Rapidly test different lens and image sensor combinations before purchasing and assembling components

Using the thin lens model, simple equations can be used to compute, compare, and analyze many camera design parameters. Insight into the trade-offs between parameters such as focal length, f/#, focus distance, image sensor Nyquist limit, hyperfocal distance, horizontal and vertical field of view, depth of field, orthogonal and normal image blur due to motion, magnification, image distance, and image pixel resolution allow designers to iterate fewer times with more confidence resulting in a system that will meet application requirements. The thin lens model sufficiently models complex lenses when the lenses have little or no distortion. When parameters cannot be modeled, they must be simulated or real-world measurements must be taken with representative components.

As camera system design capabilities increase in demand in this rapidly evolving field, Twisthink is creatively exploring the value embedded vision can bring to new products and services.For example, as a member of the Embedded Vision Alliance, Twisthink is empowering product creators to incorporate camera systems into new products and applications by applying a human-centered design approach to problem solving along side deep technical expertise in embedded systems, vision systems, and connectivity. If you are interested in learning more about the specifics of camera model design and the different equations that can be used to develop a camera system – check out my LinkedIn article here. If your team needs support specifying and designing the appropriate camera system for your application, Twisthink can help! Contact us at

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As our Director of Data Science, Ryan is responsible for bringing value to our team and clients by designing sensor solutions and data analytics pipelines that create trustworthy decisions and insights . He leads a team of talented system thinkers who approach challenges through the lenses of sensors, data, AI, and algorithms.

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