Low-Power Analog Smart Camera Sensor for Edge Detection

Conference contribution

Publication Details

Author(s): Söll C, Shi L, Röber J, Reichenbach M, Weigel R, Hagelauer A
Publication year: 2016


This work presents an intelligent analog image sensor system for smart camera applications with the need of edge or marker detection. The system consists of a 3x3 read-out CMOS image sensor, an analog Sobel stage and additional circuitry like operational amplifiers and comparators to compute a 1bit image with the edges present in the taken photo. This information can then be further processed digitally to detect specific shapes in order to control robot routines, for example. The architecture of the proposed system is highly desirable as dedicated analog hardware has significant advantages in terms of power and speed compared to digital implementations. The overall system is simulated with the help of a 3x3 CMOS image sensor IC as well as Cadence Virtuoso for analog circuit simulation and MATLAB to convert the sequential information back to an image, and compared to other state of the art CMOS image sensors with edge detection capability. The analog Sobel circuit runs with a clock of 10MHz and consumes less than 0.79mW average power for the computation of the example image, and the whole 200x200 pixel image sensor consumes only 5.5mW at a frame rate of 75 fps.

FAU Authors / FAU Editors

Hagelauer, Amelie Dr.-Ing.
Lehrstuhl für Technische Elektronik
Reichenbach, Marc Dr.-Ing.
Lehrstuhl für Informatik 3 (Rechnerarchitektur)
Röber, Jürgen
Lehrstuhl für Technische Elektronik
Shi, Lan
Lehrstuhl für Technische Elektronik
Söll, Christopher
Lehrstuhl für Technische Elektronik
Weigel, Robert Prof. Dr.-Ing.
Lehrstuhl für Technische Elektronik

How to cite

Söll, C., Shi, L., Röber, J., Reichenbach, M., Weigel, R., & Hagelauer, A. (2016). Low-Power Analog Smart Camera Sensor for Edge Detection. Phoenix, USA.

Söll, Christopher, et al. "Low-Power Analog Smart Camera Sensor for Edge Detection." Proceedings of the IEEE International Conference on Image Processing (ICIP), Phoenix, USA 2016.


Last updated on 2018-19-04 at 03:50