Abstract: An object detection method includes steps that are to be performed for each piece of point cloud data received from a lidar module, of selecting a first to-be-combined image from among images received from a camera device that corresponds in time to the piece of point cloud data, selecting a second to-be-combined image from among the images that is the Nth image before the first to-be-combined image in the time order, combining the first to-be-combined image and the second to-be-combined image to generate a combined image, generating a result image by incorporating the piece of point cloud data into the combined image, and inputting the result image into a trained machine learning model in order to determine a class to which each object in the result image belongs.

Abstract: A method for image-based dynamic feature enhancement includes: using the camera to capture multiple images, selecting an ROI from each of the multiple images displayed on the camera through the ROI selection unit, configuring multiple brightness weights to correspond to the ROI, adjusting brightness of the image according to the multiple brightness weights and multiple actual brightness values corresponding to the ROI, and performing a multi-layer progressive sharpening process to adjust multiple actual sharpening parameters of the image through the sharpening adjustment unit. The camera parameters of the camera can be directly and instantly adjusted to improve brightness and sharpening of images captured by the camera and facilitate advanced driver assistance system to clearly identify road conditions.

Abstract: A method for image-based dynamic feature enhancement includes: using the camera to capture multiple images, selecting an ROI from each of the multiple images displayed on the camera through the ROI selection unit, configuring multiple brightness weights to correspond to the ROI, adjusting brightness of the image according to the multiple brightness weights and multiple actual brightness values corresponding to the ROI, and performing a multi-layer progressive sharpening process to adjust multiple actual sharpening parameters of the image through the sharpening adjustment unit. The camera parameters of the camera can be directly and instantly adjusted to improve brightness and sharpening of images captured by the camera and facilitate advanced driver assistance system to clearly identify road conditions.

Abstract: An image processing apparatus includes an electronic device, a network and a server. The electronic device has a transmitting unit and a receiving unit, and the transmitting unit provides at least one image data. The network is connected to the electronic device for transmitting the image data. The server is connected to a network for receiving an image data. The server has an image processing unit for detecting a feature of the image data, synthesizing the image data with a media object based on the feature, retrieving the feature to perform one of the synthesis methods with the media object to generate a synthesized image data, and transmitting the synthesized image data to the receiving unit via a network.