66results about How to "Meet real-time processing requirements" patented technology

The invention discloses a sea-land clutter scene segmentation method based on energy concentration measure, and mainly aims to solve the problem that the quality of segmentation is poor in the prior art. According to the technical scheme, the method comprises the following steps: (1) emitting a pulse signal through a radar emitter, and receiving echo data through a radar receiver, wherein the echo sequence in each resolution cell of the echo data is X; (2) carrying out over-M sampling Fourier transform on X to get the frequency sequence Y of the echo sequence in each resolution cell; (3) calculating an energy concentration matrix E based on Y; (4) converting E into a gray image H, and carrying out median filtering on the gray image H; (5) using a maximum between-cluster variance threshold segmentation method to initially segment the threshold of an image H1 obtained through median filtering to get an initially-segmented image B; and (6) morphologically filtering the image B to get a final clutter scene segmentation result Z. The quality of sea-land clutter scene segmentation is improved. The sea-land clutter scene segmentation method meets the requirement of real-time scene segmentation, and can be used in sea-land clutter scene segmentation under a moving or stationary coherent system platform.

The invention relates to a multi-resolution network characteristic registration-based method for sorting face values and face directions of notes in a sorter, which comprises the following steps of: firstly, before performing image recognition and image measurement, balancing the luminance of different points on sampling images; secondly, performing Haar wavelet transform on note images, and extracting approximate picture contents of the note images; thirdly, extracting network characteristics; fourthly, analyzing the separability of the network characteristics on different note images; and finally, establishing a comprehensive sorter by using the network characteristics, wherein a structural risk minimization-based Gaussian mixture model is applied in the sorter. By the method, the real-time processing requirement of the note sorter can be met, and the requirement of processing 1,000 notes per minute can be met. Simultaneously, the defect of inconsistent note images in the same currency and face direction caused by abrasion and printing can be overcome effectively by adopting local characteristic registration so as to perform better recognition.