37 results about "Corner detector" patented technology

The method operates by estimating the differential movement of the scene picked up by a vertically-oriented camera. Estimation includes periodically and continuously updating a multiresolution representation of the pyramid of images type modeling a given picked-up image of the scene at different, successively-decreasing resolutions. For each new picked-up image, an iterative algorithm of the optical flow type is applied to said representation. The method also provides responding to the data produced by the optical-flow algorithm to obtain at least one texturing parameter representative of the level of microcontrasts in the picked-up scene and obtaining an approximation of the speed, to which parameters a battery of predetermined criteria are subsequently applied. If the battery of criteria is satisfied, then the system switches from the optical-flow algorithm to an algorithm of the corner detector type.

A directional anti-aliasing filter circuit includes an input node and an output node, a directional anti-aliasing filter having an input coupled to the input node, an adaptive gain control having an input coupled to an output of the directional anti-aliasing filter, a summer having a first input coupled to an output of the adaptive gain control, a second input coupled to the input node, and an output coupled to the output node, a texture detector for providing a texture adjust signal to the directional anti-aliasing filter and a texture adaptive gain signal to the adaptive gain control, an edge detector for providing an edge direction signal to the directional anti-aliasing filter, and a corner detector for providing a corner adaptive gain signal to the adaptive gain control.

A robot comprises a base, a first-stage slope trunk, a second-stage slope trunk, a third-stage slope trunk and a robot head. The robot head is located on a third-stage rotary top disc. A top disc of the first-stage slope trunk, a top disc of the second-stage slope trunk and the top disc of the third-stage slope trunk are all orbicular, and the diameters of all stages of top discs are gradually decreased from bottom to top. Any two stages of trunks can rotate by 360 degrees relatively. Corner detectors of all stages of trunks are arranged and used for transmitting a detection signal to a main controller. The main controller is further connected with a third-stage motor, a second-stage motor, a first-stage motor and a base motor in a controlling mode. The body language actions of the robot are smooth and high in amplitude, the structure is simple, and control is convenient.

This invention relates to a media jam and media bent corner detector, comprising: a carriage; a transducer operatively connected to or adjacent to the carriage; and a piezoelectric film beam operatively connected to the transducer such that a portion of the beam substantially extends into a media path to detect the presence of a media jam or a media bent corner.

A transmission controller includes: a corner detector that detects a corner; a predictor to predict a rolling amount based upon road data when the corner is detected and an accelerator opening degree is fully closed; a device to determine a first necessary engine braking amount in accordance with the rolling amount; a device to determine a first required speed change stage corresponding to the first necessary engine braking amount; a calculator to calculate a second necessary engine braking amount when the corner is detected and the accelerator opening degree is fully closed based upon a minimum required inter-vehicle distance with the vehicle ahead; a device to determine a second required speed change stage corresponding to the second engine braking amount; and a transmission controller to select, as a target speed change stage, either smaller one of the first or second required speed change stage, and then perform downshift control.

A circuit used for indicating process corner and extreme temperature mainly comprises a proportional to absolute temperature (PTAT) current source, a negative to absolute temperature (NTAT) current source, a constant to absolute temperature (CTAT) current source, a corner detector, a poly detector, an extreme temperature detector. The circuit can improve more power consumption without trade-off. In debug phase, the circuit can read out a state of a suspect sample and can run simulation check quickly to identify the real problem. In production phase, the circuit can easily read out at a processing station. In the mean time, a large quantity of data can be easily collected and analyzed.

The invention belongs to the technical fields of image enhancement and feature detection and particularly relates to a camera calibration relevant technology in the three-dimensional measurement field. A sub-pixel checkerboard corner detection method based on color constancy comprises the steps that a, a Harris corner detector with color constancy is proposed; and b, the sub-pixel precision cornerdetection method with illumination and color offset invariance is proposed. By the adoption of the technical characteristics, almost identical pixel precision corner positions can be obtained relative to illumination and color changes.

The invention discloses an image contour corner point detection method based on centroid distance calculation. The corner point area is located by calculating the Euclidean distance between each image contour point and the centroid of the local area formed by it. The specific steps are as follows: first read the image, and extract the edge Contour, calculate the Euclidean distance between each pixel of the image contour and the centroid of the local area formed to form a distance set G, use upper and lower limit threshold processing and point threshold processing on G to form a set I, and finally for each element in I Each point applies the Harris corner detector to calculate the response, and the coordinates of the corresponding point with the strongest response in each element are the corner points. The present invention locates the corner area by calculating the Euclidean distance between each image contour point and the centroid of the local area formed, and the calculation result is less affected by the gray scale change of the image, which strengthens the immunity to noise and reduces the generation of false corner points. This method is suitable for computer vision fields such as image registration and matching, image fusion and object recognition.