Abstract:
An image recognition method and apparatus. The method comprises: carrying out image processing and spatial transformation processing on a to-be-recognized image based on a spatial transformer network model, so as to obtain a reproduced image probability value corresponding to the to-be- recognized image; and determining the to-be-recognized image as a suspected reproduced image when it is judged that the reproduced image probability value corresponding to the to-be-recognized image is greater than or equal to a preset first threshold. By means this method, a spatial transformer network model can be established by merely carrying out one model training and model testing on a spatial transformer network. The method reduces the workload for calibrating image samples during training and testing and further enhances training and testing efficiencies. Further, the model training is carried out based on a one-level spatial transformer network, and configuration parameters obtained from the training form an optimal combination, thereby improving the recognition function when using the spatial transformer network model to recognize an image online.
Abstract:
The invention pertains to a method for transforming a set of spectral images, the method comprising: dividing the images in said set in identically arranged areas; for each of said areas, calculating a predetermined characteristic across said set of images; and, for each of said images, normalizing intensity values in each of said areas in function of said predetermined characteristic of said area. The invention also pertains to a corresponding computer program product and a corresponding image processing system.
Abstract:
An apparatus includes an object detector configured to receive image data of a scene viewed from the apparatus and including an object. The image data is associated with multiple scale space representations of the scene. The object detector is configured to detect the object responsive to location data and a first scale space representation of the multiple scale space representations.
Abstract:
A method for detecting unstructured road boundary is provided. The method may include: obtaining a color image; selecting a candidate road region within the color image according to a road model; identifying a seed pixel from the candidate road region; obtaining a brightness threshold and a color threshold, where the brightness threshold and the color threshold are determined according to brightness distances and color distances from pixels in the candidate road region to the seed pixel; and performing road segmentation by determining whether the pixels in the candidate road region belong to a road region based on the brightness threshold and the color threshold. The amount of computation can be reduced greatly by using the improved unstructured road boundary detection method.
Abstract:
Novel methods and systems for automated data analysis are disclosed. Data can be automatically analyzed to determine features in different applications, such as visual field analysis and comparisons. Anomalies between groups of objects may be detected through clustering of objects.
Abstract:
The present invention relates to automated document processing and more particularly, to methods and systems for document image capture and processing using mobile devices. In accordance with various embodiments, methods and systems for document image capture on a mobile communication device are provided such that the image is optimized and enhanced for data extraction from the document as depicted. These methods and systems may comprise capturing an image of a document using a mobile communication device; transmitting the image to a server; and processing the image to create a bi-tonal image of the document for data extraction. Additionally, these methods and systems may comprise capturing a first image of a document using the mobile communication device; automatically detecting the document within the image; geometrically correcting the image; binarizing the image; correcting the orientation of the image; correcting the size of the image; and outputting the resulting image of the document.