An Instrument for the Characterization and Calibration of Optical Sensors

Abstract

This paper presents the development of a hardware/software system for the characterization of the electronic response of optical (camera) sensors such as matrix and linear color and monochrome Charge Coupled Device (CCD) or Complementary Metal Oxide Semiconductor (CMOS). The electronic response of a sensor is required for inspection purposes. It also allows the design and calibration of the integrating device to achieve the desired performance. The proposed instrument equipment fulfills the most recent European Machine Vision Association (EMVA) 1288 standard ver. 3.1: the spatial non uniformity of the illumination ΔE must be under 3%, and the sensor must achieve an f-number of 8.0 concerning the light source. The following main innovations have achieved this: an Ulbricht sphere providing a uniform light distribution (irradiation) of 99.54%; an innovative illuminator with proper positioning of color Light Emitting Diodes (LEDs) and control electronics; and a flexible C# program to analyze the sensor parameters, namely Quantum Efficiency, Overall System Gain, Temporal Dark Noise, Dark Signal Non Uniformity (DSNU1288), Photo Response Non-Uniformity (PRNU1288), Maximum achievable Signal to Noise Ratio (SNRmax), Absolute sensitivity threshold, Saturation Capacity, Dynamic Range, and Dark Current. This new instrument has allowed a camera manufacturer to design, integrate, and inspect numerous devices and camera models (Necta, Celera, and Aria).

A framework for flexible and reconfigurable vision inspection systems

“…As shown in Fig. 2 (left side), the vision hardware mainly includes camera sensors [14], focal lenses, optical filters, port connections, lighting, and handling sub-systems. Software components include embedded computing integrated with vision data management tools and processing algorithms to perform specific visual inspection activities (Fig.…”

“…Vision systems belong to the interdisciplinary fields of system engineering or, more generally, automation [6], and incrementally benefit from the fast progress in electronics (e.g., sensors, processors, specialized cards) and computer science (e.g., algorithms) [7]. Despite the considerable level of automation introduced by these solutions, and the integration with I4.0 cutting-edge technologies such as the Internet of Things (IoT), enabling device connectivity [8]; autonomous robots, capable of self-operation [2]; big data and analytics, for data-driven insights [9]; Additive Manufacturing (AM), using 3D printing [10,11]; and Augmented Reality (AR), enhancing real-world experience [12], the reconfiguration activities (i.e., hardware setup and software parametrization) are still human-intensive based [2,13,14].…”