A method and system for segmenting touching text lines in an image of a uchen-script Tibetan historical document are provided. The method includes: first obtaining a binary image of a uchen-script Tibetan historical document after layout analysis; detecting local baselines in the binary image, to generate a local baseline information set; detecting and segmenting a touching region in the binary image according to the local baseline information set, to generate a touching-region-segmented image; allocating connected components in the touching-region-segmented image to corresponding lines, to generate a text line allocation result; and splitting text lines in the touching-region-segmented image according to the text line allocation result, to generate a line-segmented image. In the present disclosure, touching text lines in a Tibetan historical document can be effectively segmented, and text line segmentation efficiency of the Tibetan historical document is improved.

Systems and methods are provided for processing and extracting content from an image captured using a mobile device. In one embodiment, an image is captured by a mobile device and corrected to improve the quality of the image. The corrected image is then further processed by adjusting the image, identifying the format and layout of the document, binarizing the image and extracting the content using optical character recognition (OCR). Multiple methods of image adjusting may be implemented to accurately assess features of the document, and a secondary layout identification process may be performed to ensure that the content being extracted is properly classified.

Systems and methods are provided for processing and extracting content from an image captured using a mobile device. In one embodiment, an image is captured by a mobile device and corrected to improve the quality of the image. The corrected image is then further processed by adjusting the image, identifying the format and layout of the document, binarizing the image and extracting the content using optical character recognition (OCR). Multiple methods of image adjusting may be implemented to accurately assess features of the document, and a secondary layout identification process may be performed to ensure that the content being extracted is properly classified.

A jump counting method for jump rope is provided. The jump counting method comprises: S1, obtaining an original video data of a jump rope movement, and extracting an audio data and an image data from the original video data; S2, calculating the number of jumps of the rope jumper according to an audio information and an image information extracted from the audio data and the image data; and S3, outputting and displaying the calculation result.

A method for generating an object detection dataset and a computer implemented object detection system are disclosed. The method comprises:

receiving a training image dataset comprising a plurality of images that include objects of interest, each image comprising pixel values corresponding to an imaged material generated by a penetrating imager;

generating a thresholded image for each of the plurality of images;

segmenting each thresholded image into images corresponding to objects;

creating a greyscale image per object from the segmented images corresponding to that object by, for each object, calculating an average pixel value for each pixel of the object from corresponding pixels of the object in the segmented images;

forming a greyscale image for the object from the averaged pixels;

storing the greyscale images in a data repository as an object detection dataset.

A system and method of analysing drilling cuttings using image data output from a hyperspectral imaging device and at least one optical camera, includes generating a hyperspectral imaging data set including a plurality of lines of hyperspectral data derived from line images taken by the hyperspectral imaging device positioned along a drilling fluid cuttings path, obtaining tracking information in respect of particles of interest from the output of the at least one optical camera, correcting the position of pixels associated with particles of interest in the plurality of lines of hyperspectral imaging data based on the obtained tracking information to generate corrected hyperspectral imaging data, and analysing the corrected hyperspectral imaging data to characterise the cuttings.

A system and method of analysing drilling cuttings using image data output from a hyperspectral imaging device and at least one optical camera, includes generating a hyperspectral imaging data set including a plurality of lines of hyperspectral data derived from line images taken by the hyperspectral imaging device positioned along a drilling fluid cuttings path, obtaining tracking information in respect of particles of interest from the output of the at least one optical camera, correcting the position of pixels associated with particles of interest in the plurality of lines of hyperspectral imaging data based on the obtained tracking information to generate corrected hyperspectral imaging data, and analysing the corrected hyperspectral imaging data to characterise the cuttings.

A space debris observation method based on alternating exposure times of a charge coupled device (CCD) camera is provided. The present disclosure controls the CCD camera to acquire consecutively and alternately short-exposure and long-exposure images based on preset exposure times. The present disclosure realizes detection and astronomical positioning of low-orbit, medium-orbit and high-orbit space debris by processing short-exposure images of odd-numbered frames. The present disclosure realizes detection of medium-orbit and high-orbit space debris by processing long-exposure images of even-numbered frames, and realizes astronomical positioning of the medium-orbit and high-orbit space debris detected in a current frame through plate constant model coefficients of adjacent odd-numbered frames. In addition, in a search mode, the present disclosure realizes precise astronomical positioning of low-orbit, medium-orbit and high-orbit space debris through a multi-point adjustment method and the plate constant model coefficients of adjacent odd-numbered frames.

Disclosed are a CAM-based weakly supervised object localization device and method. The device includes: a feature map extractor configured to extract a feature map of a last convolutional layer in a convolutional neural network (CNN) in a process of applying an image to the CNN; a weight vector binarization unit configured to first binarize a weight vector of a linear layer in a process of sequentially applying the feature map to a pooling layer that generates a feature vector and the linear layer that generates a class label; a feature map binarization unit configured to second binarize the feature map based on the first binarized weight vector; and a class activation map generation unit configured to generate a class activation map for object localization based on the second binarized feature map.

At least some embodiments of the present disclosure directs to a method for processing an input image having an embedded element, comprising the steps of: computing one or more histograms of the input image; identifying a range of interest in one of the one or more histograms; and determining, by the processor, a threshold based on the range of interest. In some embodiments, a computing device processes the input image using the threshold to generate an output image.