8 results about "Grayscale" patented technology

A power system for an organic light emitting diode (OLED) display includes a power supplier and a power source controller. The power supplier respectively supplies a first power source voltage and a second power source voltage to first and second power source voltage application lines. The power source controller calculates a reference power source voltage corresponding to a maximum average grayscale using a distribution for each grayscale of first to third image data, models each voltage drop of the first and second power source voltages for first to third subpixels, and reflects the voltage drop to the reference power source voltage to change the second power source voltage.

The invention discloses an image retrieval method comprising the following steps of: firstly, carrying out grey level transformation and noise reduction treatment on a scene image acquired by an image module to obtain a scene grey image; then, detecting a target object outline in the scene grey image; and finally, updating the target grey image or the feature description of the target grey image in the target object outline to an image retrieval server end for image retrieval. Correspondingly, the invention also discloses an image retrieval device, a mobile terminal and an image retrieval system. Before image retrieval, a target object is extracted precisely through outline detection, so that the influence of an image background to an image retrieval result is effectively reduced, and the retrieval precision is improved.

The invention discloses an image segmentation method for flaw detection of a cell tail end. Firstly, an initial BGR image at the cell tail end is converted into a gray scale image by considering image characteristics of intelligent flaw detection of the cell tail end, then the gray scale image is subjected to binaryzation processing so as to obtain a binaryzation image, and then coordinates of four key pixel points on the outer contour of the cell tail end are determined on the binaryzation image. The size of an ROI rectangular area where the cell tail end exists is determined according to the coordinates of the four key pixel points on the outer contour of the cell tail end, therefore the ROI rectangular area where the cell end tail exists is marked off in the initial BGR image, and a target area is not damaged. High accuracy in image dividing is ensured, operation is simple, and an early-stage guarantee is provided for accuracy of follow-up processing algorithms (such as the image characteristic extracting and matching algorithm). In addition, the ROI rectangular area is marked off in the initial BGR image, so that the processing of the whole image comprising the background with the follow-up processing algorithms is avoided, detecting efficiency of a cell is improved, and detecting cost is reduced.

The invention provides a method and a system for recognizing dorsal hand vein based on in-bit-plane block mutual information. The method and the system generate eight bit-plane maps from gray-scale images retaining the dorsal hand vein contour, and extract the mutual information of the blocks in the bit-plane maps as features, so that the method has high robustness to image distortion and the like, high intra-class correlation and low inter-class correlation of the features, good separability, and high recognition rate.

The invention discloses a face feature extraction method of a self-adaptive extension cross type local binary pattern. An existing method is not stable enough in feature extraction result and not strong in robustness due to fixed threshold value or single and unbalanced key point sampling. The method comprises the following steps: firstly, preprocessing an input face image to obtain a standard single face grayscale image; determining a local neighborhood and a central pixel; the method comprises the following steps: selecting four inner-layer pixels and four outer-layer pixels, calculating anadaptive threshold according to a normalized linear weighting mode, taking any inner-layer pixel in eight pixels as a starting point, sequentially taking all pixels from the inner-layer pixels to theouter-layer pixels at intervals, comparing with the adaptive threshold, encoding according to a comparison result, and converting into a decimal encoding value; and traversing all the pixels to obtaina local binary pattern coding feature map of the face. According to the method, under various interferences such as illumination, postures, expressions and shielding, the extracted features show goodrobustness, and the method has practical application value for face recognition.