The present disclosure provides a face image quality evaluating method as well as an apparatus and a computer-readable storage medium using the same. The method includes: obtaining a face image; determining a local bright area in the face image, wherein the local bright area is formed by an illumination source in the face image, and the brightness of the local bright area is greater than the brightness of a face area in the face image; removing the local bright area from the face image; and evaluating a quality of the face image based on the face image having removed the local bright area. In the above-mentioned manner, the present disclosure improves the accuracy of the quality evaluation of the face image.

A background image is acquired by imaging an opening plate as a background of an original document in a state where the original document is not arranged. Next, an original document including background image is acquired by imaging the same range as the background image in a state where the original document is arranged on an upper surface of the opening plate. Next, a difference image is generated by subtracting the background image from the original document including background image. In addition, an inverse difference image is generated by subtracting the original document including background image from the background image. A region of the original document is detected based on the difference image and the inverse difference image.

A system and process for extracting information from filled form images is described. In one example the claimed invention first extracts textual information and the hierarchy in a blank form. This information is then used to extract and understand the content of filled forms. In this way, the system does not have to analyze from the beginning each filled form. The system is designed so that it remains as generic as possible. The number of hard coded rules in the whole pipeline was minimized to offer an adaptive solution able to address the largest number of forms, with various structures and typography. The system is also created to be integrated as a built-in function in a larger pipeline. The form understanding pipeline could be the starting point of any advanced Natural Language Processing application.

Devices, systems, and methods of generating and providing a target topographic map for finishing a photomask blank are disclosed. A method includes receiving topographic data corresponding to an uncompleted photomask blank, receiving functional specifications for flatness of an acceptable photomask blank, and generating the target topographic map for first and/or second major surfaces of the blank, which provides instructions for removing material from the first and/or second major surfaces such that the first and second major surfaces achieve a flatness that passes each functional specification. The amount of material removed reflects a reduction in material necessary to pass the functional specifications. The method further includes transmitting the target topographic map to the finishing device to utilize a finishing technique to implement changes to the photomask blank according to the target topographic map by removing the material from the photomask blank to achieve a photomask blank that passes the functional specifications.

Techniques are disclosed for extracting micro-features at a pixel-level based on characteristics of one or more images. Importantly, the extraction is unsupervised, i.e., performed independent of any training data that defines particularly objects, allowing a behavior-recognition system to forgo a training phase and for object classification to proceed without being constrained by specify object definitions. A micro-feature extractor that does not require training data is adaptive and self-trains while performing the extraction. The extracted micro-features are represented as a micro-feature vector that may be input to a micro-classifier which groups object into object type clusters based on the micro-feature vectors.

Disclosed is a method and apparatus for determining a lane, the method including extracting plural straight-line segments from a captured stereo image including a first image and a second image of a driving road, selecting a first lane from the stereo image based on line segments of the plural straight-line segments, corresponding to lanes of the driving road, predicting a second lane candidate, based on the first lane, including at least a portion of a lane area excluding the line segments in the stereo image, and determining a second lane by updating a position of the predicted second lane candidate based on a confidence value of the predicted second lane candidate.

Described are systems and methods for determining an agent that performed an event within a materials handling facility. A series of overhead images that include representations of the event location and one or more agents are processed to determine a motion or movement of the agent over a period of time. For example, a motion model representative of a motion of the agent over a period of time is generated from the images. A distance between the motion model and the event location is also determined. An association between the agent and the event may be determined based on the motion model and the distance between the motion model and the event location.

A system and process for extracting information from filled form images is described. In one example the claimed invention first extracts textual information and the hierarchy in a blank form. This information is then used to extract and understand the content of filled forms. In this way, the system does not have to analyze from the beginning each filled form. The system is designed so that it remains as generic as possible. The number of hard coded rules in the whole pipeline was minimized to offer an adaptive solution able to address the largest number of forms, with various structures and typography. The system is also created to be integrated as a built-in function in a larger pipeline. The form understanding pipeline could be the starting point of any advanced Natural Language Processing application.

The present disclosure provides an object detection method and an object detection device. The object detection device includes: a heterogeneous processor and a memory, the heterogeneous processor including: a processing unit and a programmable logic unit, wherein the programmable logic unit is configured to receive a to-be-detected image, perform feature extraction on the to-be-detected image, and write an extracted feature into the memory; the processing unit is configured to read the feature from the memory, perform target object detection according to the feature, and output a detection result to the programmable logic unit; and the programmable logic unit is further configured to receive the detection result, generate prompt information according to the detection result, and output the prompt information.

There is provided an encoding device, encoding method, decoding device, and decoding method that make it possible to improve the coding efficiency. The encoding device and the decoding device each perform classification of classifying a pixel of interest of a decoding in-progress image into any of a plurality of classes by using an inclination feature amount, and perform a filter arithmetic operation with the decoding in-progress image by using a tap coefficient of a class of the pixel of interest among tap coefficients of the respective classes. The inclination feature amount indicates a tangent direction of a contour line of pixel values of the pixel of interest. The decoding in-progress image is obtained by adding a residual of predictive coding and a predicted image together. The tap coefficients of the respective classes are each obtained through learning for minimizing an error by using the decoding in-progress image and an original image. The original image corresponds to the decoding in-progress image. The present technology is applicable in a case where an image is encoded or decoded.