A system and method for image processing are provided. A pre-processed image may be obtained. The pre-processed image may be decomposed into a low-frequency image and a high-frequency image. At least one grayscale transformation range may be determined based on the low-frequency image. At least one grayscale transformation parameter may be determined based on the at least one grayscale transformation range. The low-frequency image may be transformed based on the at least one grayscale transformation parameter to obtain a transformed low-frequency image. A transformed image may be generated by reconstructing the transformed low-frequency image and the high-frequency image.

To estimate the top surface of a measurement target on the basis of a data point group that corresponds to the top surface of a measurement target and is obtained using a laser scanner. This top surface estimation method for hoisting loads and by acquiring, using the laser scanner, data point groups in a hoisting load region which includes a hoisting load and an object from above the hoisting load and the object, dividing the hoisting load region into layers which constitute a plurality of groups which have a prescribed thickness in the vertical direction, and allocating the acquired data point groups to the plurality of layer groups, and estimating the top surfaces of the hoisting load and the object in each layer group on the basis of the data point groups allocated to the plurality of layer groups.

To estimate the top surface of a measurement target on the basis of a data point group that corresponds to the top surface of a measurement target and is obtained using a laser scanner. This top surface estimation method for hoisting loads and by acquiring, using the laser scanner, data point groups in a hoisting load region which includes a hoisting load and an object from above the hoisting load and the object, dividing the hoisting load region into layers which constitute a plurality of groups which have a prescribed thickness in the vertical direction, and allocating the acquired data point groups to the plurality of layer groups, and estimating the top surfaces of the hoisting load and the object in each layer group on the basis of the data point groups allocated to the plurality of layer groups.

A method for generating a multi-modal video dataset with pixel-wise hand segmentation is disclosed. To address the challenges of conventional dataset creation, the method advantageously utilizes multi-modal image data that includes thermal images of the hands, which enables efficient pixel-wise hand segmentation of the image data. By using the thermal images, the method is not affected by fingertip and joint occlusions and does not require hand pose ground truth. Accordingly, the method can produce more accurate pixel-wise hand segmentation in an automated manner, with less human effort. The method can thus be utilized to generate a large multi-modal hand activity video dataset having hand segmentation labels, which is useful for training machine learning models, such as deep neural networks.

A method for generating a multi-modal video dataset with pixel-wise hand segmentation is disclosed. To address the challenges of conventional dataset creation, the method advantageously utilizes multi-modal image data that includes thermal images of the hands, which enables efficient pixel-wise hand segmentation of the image data. By using the thermal images, the method is not affected by fingertip and joint occlusions and does not require hand pose ground truth. Accordingly, the method can produce more accurate pixel-wise hand segmentation in an automated manner, with less human effort. The method can thus be utilized to generate a large multi-modal hand activity video dataset having hand segmentation labels, which is useful for training machine learning models, such as deep neural networks.

A method for segmenting images is provided including tessellating an image obtained from one of an image database and an imaging system into a plurality of sectors; classifying each of the plurality of sectors by applying one or more pre-defined labels to each of the plurality of sectors, wherein the pre-defined labels indicate at least one of an image quality metric (IQM) and a metric of structure; assigning each of the plurality of classified sectors an Image Quality Classification (IQC); identifying anchor sectors among the plurality of classified sectors, applying filtering and edge detection to identify target boundaries; applying contouring across contiguous sectors and using the assigned IQC as a guide to complete segmentation of an edge between any two identified anchor sectors; and smoothing across segmented regions to increase parametric second-order continuity.

A method for managing image data in an automotive lighting device. This method includes the steps of providing an image pattern, dividing the image pattern in rows or columns of pixels, and providing, for each row pattern, a plurality of linear segments. Also included is providing a breaking pixel, splitting a segment by the breaking pixel, compressing the data of the linear segments and sending the compressed data to the light module. The invention also provides an automotive lighting device for performing the steps of such a method.

A method for managing image data in an automotive lighting device. This method includes the steps of providing an image pattern, dividing the image pattern in rows or columns of pixels, and providing, for each row pattern, a plurality of linear segments. Also included is providing a breaking pixel, splitting a segment by the breaking pixel, compressing the data of the linear segments and sending the compressed data to the light module. The invention also provides an automotive lighting device for performing the steps of such a method.

An image processing apparatus extracts a foreground image corresponding to an object included in a processing image using a background image corresponding to the processing image, and generates the background image from the processing image. The image processing apparatus determines whether it is allowed to update the background image for use in the extraction, and based on a result of the determination, updates the background image for use in the extraction using the generated background image.

The present invention provides a method for the analysis of a tribofilm, said process comprising: a. obtaining an image of the tribofilm using a digital imaging device b. coding each pixel in the image according to the RGB colour of said pixel; c. assigning a tribofilm thickness to each pixel on the basis of the RGB colour of said pixel to produce a tribofilm thickness data point for each pixel; d. excluding all data points for parts of the image where the thickness of the tribofilm is zero or near-zero; and e. analysing the resultant individual tribofilm thickness data points.