43 results about "Gradient analysis" patented technology

Locating an eye includes generating an intensity response map by applying a 3-rectangle filter and applying K-mean clustering to the map to determine the eye. Locating an eye corner includes applying logarithm transform and grayscale stretching to generate a grayscale eye patch, generating a binary map of the patch by using a threshold based on a histogram of the patch, and estimating the eye corner by averaging coordinates weighted by minimal eigenvalues of spatial gradient matrices in a search region based on the binary map. Locating a mouth corner includes generating another intensity response map and generating another binary map using another threshold based on another histogram of the intensity response map. Locating a chin or a cheek includes applying angle constrained gradient analysis to reject locations that cannot be the chin or cheek. Locating a cheek further includes removing falsely detected cheeks by parabola fitting curves through the cheeks.

Concurrent Gradients Analysis (CGA), and two multi-objective optimization methods based on CGA are provided: Concurrent Gradients Method (CGM), and Pareto Navigator Method (PNM). Dimensionally Independent Response Surface Method (DIRSM) for improving computational efficiency of optimization algorithms is also disclosed. CGM and PNM are based on CGA's ability to analyze gradients and determine the Area of Simultaneous Criteria Improvement (ASCI). CGM starts from a given initial point, and approaches the Pareto frontier sequentially stepping into the ASCI area until a Pareto optimal point is obtained. PNM starts from a Pareto-optimal point, and steps along the Pareto surface in the direction that allows improving a subset of objective functions with higher priority. DIRSM creates local approximations based on automatically recognizing the most significant design variables. DIRSM works for optimization tasks with virtually any (small or large) number of design variables, and requires just 2-3 model evaluations per Pareto optimal point for the CGM and PNM algorithms.

A methodology for reservoir understanding employs analysis of fluid property gradients to investigate and distinguish between non-compartmentalization of the reservoir, compartmentalization of the reservoir, and lack of thermodynamic equilibrium in the reservoir.

A method of detecting a presence or absence of subject matter of interest, for example, sheet explosives and / or other potential threat objects is provided by various local and / or global gradient analysis methods including determining characteristics of gradient information of regions in an X-ray image to determine if the regions are associated with subject matter of interest for which detection may be desired, for example, contraband, explosives and / or other prohibited or unauthorized material.

The invention discloses an image restoring method and device. The method comprises the following steps of: step A, obtaining a first layer region to be restored of an image damaged region from inside to outside, and reading structural information and a color of the known image region which is close to the first layer region to be restored; step B, carrying out gradient analysis and color estimation on the first layer region to be restored according to the structural information and the color of the known image region to obtain gradient information and a color of the first layer region to be restored; step C, taking the gradient information and the color of the first layer region to be restored as initial values to be extended to the first layer region to be restored; step D, carrying out texture synthesis restoration on the first layer region to be restored according to the initial values to obtain a first restoring result; and step E, taking the first restoring result as the known image region to circularly execute the steps A to D until the image damaged region is restored. With the adoption of the image restoring method and device, disclosed by the invention, the structural region can be accurately positioned, the block matching accuracy is improved, and the introduction and the reproduction of error information are reduced.

A detector for liquid chromatography has light sources that generate light in an ultraviolet region and in a near-infrared region; a flow cell, through which sample liquid flows; an optical system to let light generated from the light sources become incident on the flow cell concurrently; a detection element that detects light in the ultraviolet region that passes through the flow cell; a detection element that detects light in the near-infrared region that passes through the flow cell; and an arithmetic operation part that performs arithmetic operation of a first signal value obtained from the detection element and of a second signal value obtained from the detection element. The arithmetic operation part combines the first signal value and the second signal value to calculate a signal value with a reduced baseline fluctuation resulting from a mobile phase during a gradient analysis.

The invention discloses a method for preprocessing noise reduction and block effect removal in low bit-rate video application. The method comprises the following steps: analyzing gradient by matrix eigenvalue; carrying out edge detection by a gradient analysis module; carrying out corrosion operation on a gradient map corresponding to an initial image to eliminate a gradient point generated by single noise; carrying out expansive operation to connect edges corresponding to the gradient point; performing motion detection by adopting a motion detection module to evaluate the motion area of the image; and selecting a two-sided filter with proper strength for filtration by adopting a filter strength determine module according to the code rate, gradient and motion characteristic. Two parametersof the two-sided filter are grey difference information and distance information. The method not only reduces noise, filters unimportant details for high efficient compression, avoids generation of the block effect, but also can play the effect of code rate control in certain degree.

The invention discloses a high-precision monitoring method for cyanobacterial blooms in a large shallow lake through an MODIS (Moderate Resolution Imaging Spectroradiometer) and a satellite. The high-precision monitoring method is characterized by comprising the following steps: screening recognition indexes of the cyanobacterial blooms (short for algal blooms) which are insensitive to the type and thickness of an atmospheric aerosol; combining the synchronous MODIS, LandsatTM / ETM and satellite image in 2000-2013 year and a gradient analysis result of land and water information to obtain a pure pixel index threshold value of the algal blooms; precisely calculating the area of the algal blooms in a mixed pixel (part of pixels covered by the algal blooms) of the algal blooms by using a pixel growth algorithm (APA); and furthermore, estimating the actual area of the algal blooms in the total water area of the lake and the areal distribution of the algal blooms. The high-precision monitoring method can be used for precisely obtaining the spatial and temporal distribution of the algal blooms in the shallow lake, accurately analyzing the generation and development condition and trend of the algal blooms, scientifically estimating the lake pollution control and ecological remediation effects and providing the scientific and technological support for making a scientific decision for water resource management and water environment protection of departments of water conservation, environment protection and the like.

A liquid chromatograph control system for controlling an operation of a liquid chromatograph which uses a mobile phase composed of a mixture of solvents and which has the function of performing a gradient analysis while temporally changing the mixture ratio of the solvents. The system initially requests a user to set a basic gradient profile (Step S12), and subsequently, to set the number of steps to change the mixture ratio of the mobile phase at the beginning and / or at the end of the gradient process as well as the amount of change in the mixture ratio per step (Step S13). After that, based on the possible combinations of the mixture ratios of the mobile phase at the beginning and at the end of the gradient process computed from the contents of information entered in the previous steps, a plurality of gradient profiles corresponding to those combinations are created (Step S14).