Abstract
The number of camera-based advanced driver assistance systems is growing steadily. Starting with rear-view cameras and ranging to complete 360° surround view systems. Such systems are not limited to displaying the captured video signals but also permit additional functions such as object detection based on the video signals. In the future, such systems will become mandatory, as have the rear-view cameras for new passenger cars in the US market. Another example is the new international standard ISO 16505 that describes the replacement of mandatory vehicle mirrors with camera monitor systems. These new technologies can be the base of future innovations for indirect vision. In order to evaluate and compare such systems, specific emphasis has to be given to the appropriate Image Quality (IQ) criteria in addition to the normative criteria.This work introduces a prototype vehicle setup utilizing a High Dynamic Range (HDR) camera for a rear-view driver assistance application. While the system shows promising results in daylight conditions, there are still several issues that are of concern when it comes to twilight, low-light, and night applications. A newly defined IQ assessment set is used for a real-time analysis of laboratory and outdoor scenes. Further, an optimization using the implemented modules in an automotive framework is performed and presented.
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Abbreviations
- AACDG:
-
Average Absolute Color Deviation from Greyscale
- ADTF:
-
Automotive Data and Time-Triggered Framework
- AWB:
-
Auto White Balancing
- CCD:
-
Charge-coupled device
- CMOS:
-
Complementary Metal Oxide Semiconductor
- CT:
-
Color Temperature
- FPGA:
-
Field Programmable Gate Array
- HDR:
-
High Dynamic Range
- HVS:
-
Human Visual System
- IQ:
-
Image Quality
- LDR:
-
Low Dynamic Range
- LED:
-
Light-Emitting Diode
- LVDS:
-
Low Voltage Differential Signaling
- MSE:
-
Mean Squared Error
- MTF:
-
Modulation Transfer Function
- PSNR:
-
Peak Signal-to-Noise Ratio
- RAM:
-
Random Access Memory
- RGB:
-
Red Green Blue
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Leznik, M., Terzis, A. (2016). Optimization of Demanding Scenarios in CMS and Image Quality Criteria. In: Terzis, A. (eds) Handbook of Camera Monitor Systems. Augmented Vision and Reality, vol 5. Springer, Cham. https://doi.org/10.1007/978-3-319-29611-1_14
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DOI: https://doi.org/10.1007/978-3-319-29611-1_14
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