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There is no clear criterion yet for evaluating wipers based on performances of wiping raindrops and visibility in forward view. In the visibility evaluation, it is important to examine spatial frequency and contrast of forward view. In this paper, we propose a new method for evaluating wiper performances based on visibility in forward view. Spatial frequency and contrast of image in the footage which were affected by the raindrops are calculated based on them of background board which were printed stripe patterns. The variations with time of power spectrum and decreased contrast are synchronized with the motion of the wiper for the all experimental cases. These results show that to evaluate wiping performance is possible by the method which we proposed.

Nowadays, driving support systems, such as car navigation systems, are getting common and they support drivers in several aspects. It is important for driving support systems to detect the state of drivers' consciousness. Particularly, detecting drivers' drowsiness could protect drivers from danger of collisions caused by drowsy driving. In this paper, we discuss a system and a method for detecting driver's drowsiness, which use a property of blink waveforms that drivers' eye-closing time is strongly connected to their drowsiness. Moreover, our system detects the drowsiness robustly for individual differences by using three factors extracted from the individual blink waveform.

Because something to think about and conversation with someone disturb the attention to the car driving, decentralization of attention by the cellular phone call tends to decrease safety in driving. This paper presents an experimental result of the relation between the attention concentration on the cellular phone call and the change in the facial expression such as eye movements and blinks. Moreover, this paper describes a method of detecting the depth of the attention concentration from the facial expression change.

Drowsiness in car-driving relates to eye-blinking. Authors have developed the robust image capture CCD system by moving image processing for the brightness of day and night in a car, using the weak pulsed infrared LED’s light. This effect was evaluated by real circumstances in a car: darkness in night and brightness in direct sunshine. To extract upper and lower eyelids’ fringes from noises, a pair of edges from a pupil was used. The second derivative to blinking waveform was introduced to obtain the stable blinks, eliminating the different characteristics among individuals’ ones. The experiment to presume the drowsiness was referred to the steering wheel movement. This tentative experiment indicated good correlation between drowsiness and eye closure time.

In this paper, the authors describe a vehicle parking space monitoring system which uses a CCD camera. Image processing is used to report the presence of a vehicle in the individual spaces. The system is able to operate under various weather conditions and in both full daylight and artificial night lighting.

To detect the state of a driver while driving, the detection system should be applicable also to a driver who wears glasses for practical use of the system. This paper reports a method of detecting blinks of a driver who wears glasses for estimating driver's level of consciousness.