System and method for improving object identification in image

Abstract

The invention is suitable for the field of traffic safety early-warning systems, and provides a system for improving object identification in an image. The system comprises a camera module, an image acquisition module, an image analysis module and a control module. The camera module shoots all objects in front of the current car to obtain a first current frame image. The image acquisition module obtains the first current frame image. The image analysis module analyzes the first current frame image and computes the overexposure or underexposure degree of the first current frame image. The control module adjusts exposure parameters of the camera module according to the overexposure or underexposure degree. The camera module shoots again according to the adjusted exposure parameters in order to obtain a second current frame image. The image acquisition module obtains the second current frame image. The image analysis module analyzes the second current frame image and computes all objects of the second current frame image to establish a data set of all the objects. The data set of all the objects can be used for analytical calculation of traffic safety early-warning. The invention also provides a method for improving object identification in the image.

Description

technical field [0001] The invention belongs to the field of early warning systems for driving safety, and in particular relates to a system and method for improving object recognition in images in a system for improving object recognition in images. Background technique [0002] With the popularization of private cars, more and more vehicles are driving on the road, and the complexity of the road is becoming more and more serious. Driving safety has become an important issue. Currently, vision-based systems for improving object recognition in images are the most effective and safest method. However, the vision-based system for improving object recognition in images is easily affected by the light intensity of the surrounding environment. If the light is too dark, the image captured by the camera is underexposed, and the color difference between the object in the captured image and the background color is too small, making it difficult for the system to improve object recog...

AI Technical Summary

Problems solved by technology

However, due to the vision-based system for improving object recognition in images, it is easily affected by the light intensity of the surrounding environment.

If the light is too dark, the image captured by the camera is underexposed, and the color difference between the object in the captured image and the background color is too small, making it difficult for the system to improve object recognition in the image to recognize all objects in front of the current vehicle

If the light is too strong, the image captured by the camera will be overexposed, which will also make it difficult for the system to improve object recognition in the image to recognize all objects in front of the current vehicle

Sometimes although the light intensity of the surrounding environment is normal, some vehicles in front of the current vehicle are blocked by the shadow of buildings (such as viaducts), so it is still difficult for the system to improve object recognition in the image to recognize all objects in front of the current vehicle

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