Automotive Night Vision Research Articles

Night riders

Automotive night vision systems can help drivers – and cars – to see clearly when they need it most

Review of Pedestrian Detection by Video Processing in Automotive Night Vision System

Review of Pedestrian Detection by Video Processing in Automotive Night Vision System

Detection of pedestrians for far-infrared automotive night vision systems using learning-based method and head validation

To improve active automotive safety and guarantee the protection of pedestrians at night time, a fast pedestrian detection approach based on a monocular far-infrared camera for driver assistance systems is presented. According to the distribution of gray-level intensity of pedestrian samples, an adaptive local dual threshold segmentation algorithm is executed first to extract candidate regions. Then a novel entropy weighted histograms of oriented gradients (EWHOG) descriptor is proposed for effective pedestrian description in a far-infrared spectrum. For reducing the within-class variance of pedestrians located at different distances, a three-branch classifier combining EWHOG features and a support vector machine (SVM) is introduced for robust pedestrian recognition. To speed up the recognition phase, the resulting support vectors (SVs) are optimized to reduce the number of SVs used for decision-making. A further validation phase is then introduced to suppress the false alarms according to the intensity difference between pedestrians’ heads and their adjacent regions. Comparisons between our approach and conventional approaches are presented, and experimental results show that the presented pedestrian detection framework is very promising.

Brightness and Color Transfer for Infrared Images in Vehicle Night Vision System

The automotive night vision system can significantly improve the safety of driving at night by fusion of visible and infrared images. Due to the aim at helping driving at night, it’s important to develop the visibility and the consistency of the image and the real condition on the road. In this paper, visible light image is enhanced its light and shadow information based on nonlinear exponential function and the infrared image is increased its contrast by S-Retriex method. Then the enhancement images are fused and the color space of fusion image is adjusted by the reference statistical characteristics. Simulations have shown that the result image has good visual scene which retains the details of the infrared image and has original light, shadow and color information.

Automotive Night-Vision Systems How Shall They Continue?

Automotive Night-Vision Systems How Shall They Continue?

Detection of pedestrians in far-infrared automotive night vision using region-growing and clothing distortion compensation

We present a night-time pedestrian detection system based on automotive infrared video processing. Far-infrared or thermal night vision is a technology well suited for automatic detection of pedestrians at night as they generally appear warmer than the background. However, the appearance of a pedestrian in IR video can vary dramatically depending on the physical properties of the clothing they wear, the time spent adjusting to the outside environment, and the ambient temperature. We highlight the difficulties of detection in low temperatures (below 8 °C) when pedestrians typically wear highly insulating clothing, which can lead to distortion of the IR signature of the pedestrian. A pre-processing step is presented, which compensates for this clothing-based distortion using vertically-biased morphological closing. Potential pedestrians (Regions of Interest) are then segmented using feature-based region-growing with high intensity seeds. Histogram of Oriented Gradients (HOG) features are extracted from candidates and utilised for Support Vector Machine classification. Positively classified targets are tracked between frames using a Kalman filter, adding robustness and increasing performance. The proposed system adapts not just to variations between images or video frames, but to variations in appearance between different pedestrians in the same image or frame. Results indicate improved performance compared to previous HOG–SVM automotive IR pedestrian detection systems, which utilised stereo IR cameras.

Pedestrian tracking routine for passive automotive night vision systems

Purpose – This paper aims to present a new approach to implement a pedestrian tracking algorithm for a passive automotive night vision application.Design/methodology/approach – First, the basic information of passive and active night vision systems is presented, with implementation methods adopted in previous work. The proposed thermal‐image processing is a combination of seed detection, boundary detection and seed growth computations, based on a temperature thresholding scheme.Findings – The processing routine performance is assessed when implemented to a continuous sequence of thermal acquisitions, from a commercial automotive night vision module. Experimental results show good tracking performance for both pedestrians and passing vehicles.Research limitations/implications – A strategy of multi‐seed growth, directional seed growth and image fusion is proposed to improve the current tracking algorithm.Originality/value – New thermal image processing routines are applied to commercial, automotive night vi...

72.1: Automotive Night Vision System with Picture Presentation

First generation Night vision enhancement systems with image presentation in the dashboard have been introduced on the market. Far Infrared and Near Infrared systems are currently competing technologies. The camera picture is presented either with a Head-up display on the windscreen or in the dashboard region. An arbitrarily configurable LC display located in the instrument cluster was found to meet best the requirements of a quick and distraction-free reading. A precondition for a quick recognition and identification of relevant obstacles is a highcontrast and brilliant picture quality. To achieve this, picture quality improvement means have been applied. Such a setup has been selected for the new Mercedes S-Class.