Abstract:
A method of spectral-morphometric analysis of biological samples, the biological samples including substantially constant components and suspected variable components, the method is effected by the following the steps of (a) using a spectral data collection device for collecting spectral data of picture elements of the biological samples; (b) defining a spectral vector associated with picture elements representing a constant component of at least one of the biological samples; (c) using said spectral vector for defining a correcting function being selected such that when operated on spectral vectors associated with picture elements representing other constant components, spectral vectors of said other constant components are modified to substantially resemble said spectral vector; (d) operating said correcting function on spectral associated with at least the variable components for obtaining corrected spectral vectors thereof; and (e) classifying said corrected spectral vectors into classification groups.
Abstract:
A method for remote scenes classification comprising the steps of (a) preparing a reference template for classification of the remote scenes via (i) classifying a set of reference scenes via a conventional classification technique for obtaining a set of preclassified reference scenes; (ii) using a first spectral imager for measuring a spectral cube of the preclassified reference scenes; (iii) employing a principal component analysis for extracting the spectral cube for decorrelated spectral data characterizing the reference scenes; and (iv) using at least a part of the decorrelated spectral data for the preparation of the reference template for remote scenes classification; (b) using a second spectral imager for measuring a spectral cube of analyzed remote scenes, such that a spectrum of each pixel in the remote scenes is obtained; (c) employing a decorrelation statistical method for extracting decorrelated spectral data characterizing the pixels; and (d) comparing at least a part of the decorrelated spectral data extracted from the pixels of the remote scenes with the reference template.
Abstract:
A spectral bio-imaging method for enhancing pathologic, physiologic, metabolic and health related spectral signatures of an eye tissue, the method comprising the steps of (a) providing an optical device for eye inspection being optically connected to a spectral imager; (b) illuminating the eye tissue with light via the iris, viewing the eye tissue through the optical device and spectral imager and obtaining a spectrum of light for each pixel of the eye tissue; and (c) attributing each of the pixels a color or intensity according to its spectral signature, thereby providing an image enhancing the spectral signatures of the eye tissue.
Abstract:
A method and apparatus for analyzing an optical image of a scene to determine the spectral intensity of each pixel thereof, by: collecting (20) incident light from the scene; scanning (22) the incident light; passing the scanned light through an interferometer (24) which outputs modulated light corresponding to a predetermined set of linear combinations of the spectral intensity of the light emitted from each pixel; focusing the light ouputted from the interferometer on a detector array (26); and processing (28) the output of the detector array to determine the spectral intensity of each pixel thereof.
Abstract:
We have designed, built and operated an innovative JTOC system utilizing a holographic photopolymer as the square law detector to record the holographic data for one-step correlation signal requisition in real time. The resultant high-resolution, high- speed JTOC is useful to perform real-time pattern recognition. An example application that has been demonstrated is fingerprint verification.
Abstract:
In a method and apparatus for performing an analysis and other activities using one or more two- or three-dimensional representational images, presenting a two- or three-dimensional representational image containing analytical information to assist in the analytical process. One or more two- or three-dimensional representational images are created, e.g., using standard photography, holography or computer imaging, and are placed in a positioner for use by the analyst. The representational images are illuminated using a light source and the analyst utilizes the information released from the representational image to perform an analysis.
Abstract:
The invention relates to a method for analyzing coincidences of medical images by means of holographic identification and filtration. This method provides for the automated quantification of the degree of coincidence of the image of an element, structure or injury of known interpretation at each point or area of another image (obtained by the same process). This method comprises a certain combination of histogram filtering techniques with a process for the filtration and holographic identification of images. Thereby, it is possible to locate in one image the total or partial presence of elements which are similar to the searched element of knownnterpretation even when this latter element proceeds from another image (of the same type), appears in a scale of different size or orientation or is apparently concealed in a complex background. This method is particularly useful for analyzing medical images obtained through any of the available process and/or techniques (tomography, echography, magnetic nuclear resonance, radiography, etc.).
Abstract:
According to the present invention there is provided a spectral bio-imaging methods which can be used for automatic and/or semiautomatic spectrally resolved morphometric classification of cells, the method comprising the steps of (a) preparing a sample to be spectrally imaged, the sample including at least a portion of at least one cell; (b) viewing the sample through an optical device, the optical device being optically connected to an imaging spectrometer, the optical device and the imagine spectrometer being for obtaining a spectrum of each pixel of the sample; (c) classifying each of the pixels into classification groups according to the pixels spectra; and (d) analyzing the classification groups and thereby classifying the at least one cell into a cell class.
Abstract:
The invention relates to a method and an arrangement for registering fingerprint information via a sensing surface (A). The method comprises scanning part surfaces (A'1) in the sensing surface (A), checking whether the centre point (P1), with its immediate surrounding area (A''1), of each scanned part surface (A'1) is unique within the part surface (A'1) and registering a first number of centre points (P1) which, with their respective immediate surrounding areas (A''1), are unique within their respective part surfaces (A'1). The respective immediate surrounding areas (A''1) of the points and the respective part surfaces (A'1) of the points are also registered. The invention also relates to a method and an arrangement for verifying fingerprint information, in which verification is carried out on the basis of registered information relating to a fingerprint which is to be approved in the verification method. The method comprises a number of part surface (A'1) with their respective centre points (P1) in the fingerprint whose information is registered being compared with corresponding part surfaces (A'2) on the sensing surface (A). If there is a point (P2) on a part surface (A'2) on the sensing surface A which, with its immediate surrounding area (A''2), corresponds to the registered centre point (P1) including its immediate surrounding area (A''1) in the corresponding stored part surface (A'1), the point (P2) with its part surface (A'2) is approved. If a certain number of points (P2) with associated part surfaces (A'2) have been approved, these are selected for a first step in further processing.
Abstract:
A method for remote scenes classification comprising the steps of (a) preparing a reference template for classification of the remote scenes via (i) classifying a set of reference scenes via a conventional classification technique for obtaining a set of preclassified reference scenes; (ii) using a first spectral imager for measuring a spectral cube of the preclassified reference scenes; (iii) employing a principal component analysis for extracting the spectral cube for decorrelated spectral data characterizing the reference scenes; and (iv) using at least a part of the decorrelated spectral data for the preparation of the reference template for remote scenes classification; (b) using a second spectral imager for measuring a spectral cube of analyzed remote scenes, such that a spectrum of each pixel in the remote scenes is obtained; (c) employing a decorrelation statistical method for extracting decorrelated spectral data characterizing the pixels; and (d) comparing at least a part of the decorrelated spectral data extracted from the pixels of the remote scenes with the reference template.