Zhang Dongliang

Bio: Zhang Dongliang is an academic researcher. The author has contributed to research in topics: Structured light. The author has an hindex of 1, co-authored 1 publications receiving 8 citations.

CCD camera nonlinearity degree calibration method based on structured light three-dimensional measurement system

Abstract: The invention provides a CCD camera nonlinearity degree calibration method based on a structured light three-dimensional measurement system. The method comprises the steps that according to the measurement processes of the structured light three-dimensional measurement system, on the basis that a series of standard images which are projected by a projector and accord with linear distribution are collected, a standard image gray scale-camera collected image gray scale distribution curve is drawn after certain data processing so as to further calculate the nonlinearity degree of a CCD camera; because gray scale gradient is small when the standard images are grouped, and the number of images collected by the CCD camera is large, random errors are reduced, and nonlinearity degree measurement precision is improved; the CCD camera nonlinearity degree calibration method based on the structured light three-dimensional measurement system accords with conditions of the structured light three-dimensional measurement system, and is simple in calibration process, less in middle link, and accurate in nonlinearity degree calibration result.

Depth determining method and device and electronic equipment

Abstract: The embodiment of the invention provides a depth determining method and device and electronic equipment. The method comprises the following steps: acquiring a colorful image and a depth image which are acquired by a camera and then are output; carrying out image identification based on the colorful image and determining a first image region recorded with a characteristic body in the colorful image; determining a second image region corresponding to the first image region in the depth image according to a pixel corresponding relation between the colorful image and the depth image; determining a characteristic body depth value of the second image region based on depth information corresponding to a pixel in the second image region. According to the embodiment, the characteristic body depth value of the characteristic body can be obtained under the condition that the precision of the depth image is lower and the characteristic body is difficult to identify.

Single picture-based non-contact measurement method for three-dimensional topographies of objects

Abstract: The invention provides a single picture-based non-contact measurement method for three-dimensional topographies of objects. The method comprises three steps of: response correction of nonlinearity of camera CCD light intensity-gray level, evaluation function curve calibration of an out-of-focus distance and a blur width, and reconstruction of three-dimensional topography of surface of an object, wherein the nonlinearity of camera CCD light intensity-gray level is corrected through comparing a standard stripe gray level value and an image stripe gray level value after camera conversion; through a theory, a relation equation of the out-of-focus distance and the blur width is obtained; by utilizing experiment calibration, related camera parameters are obtained; evaluation curves of the out-of-focus distance and the blur width are established; by utilizing the camera parameters, an in-plane coordinate, projected to an adjacent focusing plane, of the surface of the object can be obtained; by measuring and calculating the blur width, the distance from the surface of the object to the focusing plane can be obtained; and therefore, the three-dimensional surface topography of the surface of the object can be measured according a photo.

Depth determination method, depth determination device and electronic device

Abstract: The present disclosure provides a depth determination method, a depth determination device and an electronic device. The depth determination method includes steps of: acquiring a color image and a depth image from a camera; performing image identification based on the color image, and determining a first image region of the color image where a feature object is recorded; determining a second image region of the depth image corresponding to the first image region in accordance with a correspondence between pixels of the color image and the depth image; and determining a feature depth of the feature object based on depth information corresponding to the pixels at the second image region.

Photographing device and photographing position optimizing method

Abstract: The invention discloses a photographing device and a photographing position optimizing method The method comprises the steps of acquiring parameter information calibrated by a photographing device; controlling a camera and/or a structural light source to move through a sliding module, acquiring an image set which comprises a series of images of a target object by the camera at different positions, recording and storing a series of position coordinates of the camera and the structural light source in the motion process of the camera and/or the structural light source by the position sensors; acquiring an image frame which has highest matching degree to the image set in the image set through the processor, and determining the position coordinate of the camera and the structural light sourcewhich correspond with the image frame with highest matching degree as the optimal photographing position The photographing device and the photographing position optimizing method realize automatic finding of the optimal photographing position of the structural light source and the camera according to the objects with different size and different distances, and furthermore improve displaying quality of the photographed image

Quality detection method and system of image sensor

Abstract: The invention provides a quality detection method and system of an image sensor, a terminal device, and a computer readable storage medium. The quality detection method comprises the following steps:obtaining a preset light emitting time of a light source in the detection system in a first preset scene; obtaining pixel values for N times within the preset light emitting time; respectively obtaining difference values between the N pixel values and a first pixel value; performing normalization processing on the N difference values to obtain N first parameters; respectively calculating a changevalue of a corresponding first parameter adjacent to a preset time interval; calculating a degree of linearity of the image sensor to be detected according to the change value of the first parameter;and judging the quality of the image sensor to be detected according to the degree of linearity. In the quality detection method provided by the embodiment of the invention, the degree of linearity of the image sensor is calculated according to the change value of the first parameter, and the quality of the image sensor is judged according to the degree of linearity, so that the accuracy and theefficiency of detecting the quality of the image sensor can be improved.