Pulse analysis using ordinal value filtering
First Claim
1. A method of pulse analysis applied to a signal conglomerate represented as a set of data samples in order to remove unwanted signals from wanted signals, comprising the following steps of:
- a) ordinal value filtering at least a selected part of the signal conglomerate with a succession of filters of window sizes increasing from N (being less than M) up to M, an input to each successive filter being formed from an output of a previous filter;
b) subtracting a current filter output from the previous filter output for said succession of filters to obtain bandpass outputs, known as granularities, consisting of strings of data points which contain strings of zero-valued data points, known as zero segments, and strings of non-zero-valued data points, known as non-zero segments or granules;
c) selecting a subset of the granularities; and
d) adding together granularities within said subset to produce an output signal containing the granules in said subset.
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Accused Products
Abstract
An image and pulse analysis system and method including a datasieve comprising a succession of ordinal filtering means receiving at least a selected part of a signal conglomerate and filtering the at least a selected part of the signal conglomerate to produce a bandpass filter output, the ordinal filtering means having window lengths increasing from N (less than M) up to M, whereby an input signal to each successive filtering means is formed from the output of the previous filtering means; selection means for selecting a predetermined subset of bandpass filter outputs from outputs of the succession of filtering means; and arithmetic means for adding together the signals of the subset to produce an output signal containing only wanted signals determined by the selection means; data storage means for storing data relating to a sought-for-feature or object which may exist in a field from which data is derived for presenting to the datasieve; comparison means for matching or comparing the stored data with the output signal of the datasieve; and selection means to select from the input signal only data having a high degree of match to the data in the data storage means.
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Citations
39 Claims
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1. A method of pulse analysis applied to a signal conglomerate represented as a set of data samples in order to remove unwanted signals from wanted signals, comprising the following steps of:
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a) ordinal value filtering at least a selected part of the signal conglomerate with a succession of filters of window sizes increasing from N (being less than M) up to M, an input to each successive filter being formed from an output of a previous filter; b) subtracting a current filter output from the previous filter output for said succession of filters to obtain bandpass outputs, known as granularities, consisting of strings of data points which contain strings of zero-valued data points, known as zero segments, and strings of non-zero-valued data points, known as non-zero segments or granules; c) selecting a subset of the granularities; and d) adding together granularities within said subset to produce an output signal containing the granules in said subset. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method of pulse analysis applied to a signal conglomerate including:
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flagging segments of the signal conglomerate which are extrema; identifying those segments which require processing by the length of the flagged segments; and processing the identified segments by ordinal value filtering where the identified segments are filtered with a succession of filtering stages of increasing window sizes, with an input to each successive filtering stage being formed from an output of a previous filtering stage. - View Dependent Claims (12, 13, 14, 15, 16, 17)
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- 18. A method of pulse analysis applied to a signal conglomerate including an ordinal value filtering step wherein at least a selected part of the signal conglomerate is filtered with a succession of ordinal value filters of increasing window sizes, an input to each successive ordinal value filter is formed from the output of the previous ordinal value filter, and at least one of the ordinal value filters is a stack filter having stages which contain positive boolean logic for reducing the amount of filtering.
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21. A method of pattern recognition which comprises the steps of:
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a successive ordinal value filtering step to filter data which describes a field containing a plurality of objects using a succession of filters of increasing window sizes, whereby an input to each successive filter is formed from the output of a previous filter so as to produce resulting data; a matching step involving matching or comparing said resulting data with data describing one particular object which is to be identified according to shape and/or pattern and/or size from the said plurality of objects; and a generation step wherein an output signal containing data relating only to objects having the characteristics of said particular object is generated. - View Dependent Claims (22, 23, 24, 25, 26, 27)
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28. A datasieve for removing unwanted signals from a signal conglomerate comprising:
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a succession of ordinal filtering means receiving at least a selected part of said signal conglomerate and filtering said at least a selected part of said signal conglomerate to produce a bandpass filter output, the ordinal filtering means having window lengths increasing from N (less than M) up to M, whereby an input to each successive ordinal filtering means is formed from the output of the previous ordinal filtering means; selection means for selecting a predetermined subset of bandpass filter outputs from outputs of the succession of ordinal filtering means; and arithmetic means for adding together the signals of the subset to produce an output signal containing only wanted signals selected by the selection means.
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29. The use of a datasieve as a picture signal decomposition element in an image analysis system adapted to perform pattern recognition, the datasieve comprising:
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a succession of ordinal filtering means receiving at least a selected part of a signal conglomerate and filtering at least a selected part of said signal conglomerate to produce a bandpass filter output, the ordinal filtering means having window lengths increasing from N (less than M) up to M, whereby an input to each successive ordinal filtering means is formed from an output of the previous ordinal filtering means; selection means for selecting a predetermined subset of bandpass filter outputs from said outputs of the succession of ordinal filtering means; and arithmetic means for adding together the signals of the subset to produce an output signal containing only signals selected by the selection means, where the input to the datasieve is data which describes a field of view containing a plurality of objects.
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30. An image analysis system incorporating:
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a datasieve comprising;
a succession of ordinal filtering means receiving at least a selected part of a signal conglomerate, said filtering said at least a selected part of said signal conglomerate to produce a bandpass filter output, the ordinal filtering means having window lengths increasing from N (less than M) up to M, whereby an input signal to each successive filtering means is formal from the output of the previous filtering means;
selection means for selecting a predetermined subset of bandpass filter outputs from outputs of the succession of filtering means; and
arithmetic means for adding together the signals of the subset to produce an output signal containing only wanted signals determined by the selection means;data storage means for storing data relating to a sought-for-feature or object which may exist in a field from which data is derived for presenting to the datasieve; comparison means for matching or comparing the stored data with the output signal of the datasieve; and selection means to select from the input signal only data having a high degree of match to the data in the data storage means. - View Dependent Claims (31, 37)
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32. A method of image analysis in which:
a data stream representative of a field of view is analyzed to identify one or more images of objects in the field of view by the following steps of; a) ordinal value filtering at least a selected part of a signal conglomerate with a succession of filters of window sizes increasing from N (being less than M) up to M, an input to each successive filter being formed from an output of a previous filter; b) subtracting a current filter output from the previous filter output for said succession of filters to obtain bandpass outputs, known as granularities, consisting of strings of data points which contain strings of zero-valued data points, known as zero segments, and strings of non-zero-valued data points, known as non-zero segments or granules; c) selecting a subset of the granularities; d) adding together granularities within said subset to produce an output signal containing the granules in said subset; and e) matching said output signal with a target or template of a particular object to be identified. - View Dependent Claims (33, 34, 35, 36)
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38. A method of pulse analysis, comprising the following steps of:
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a) ordinal value filtering at least a selected part of a signal conglomerate with a succession of filters of window sizes increasing from N (being less than M) up to M, an input to each successive filter being formed from an output of a previous filter; b) subtracting a current filter output from the previous filter output for said succession of filters to obtain bandpass outputs, known as granularities, consisting of strings of data points which contain strings of zero-valued data points, known as zero segments, and strings of non-zero-valued data points, known as non-zero segments or granules; c) selecting a subset of the granularities; d) adding together granularities within said subset to produce an output signal containing the granules in said subset; e) selecting the signals passed by the Mth ordinal filter; and f) combining the selected signals with only some of the granules obtained from the preceding steps.
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39. The use of a method of pulse analysis comprising the following steps of:
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a) ordinal value filtering at least a selected part of a signal conglomerate with a succession of filters of window sizes increasing from N (being less than M) up to M and with the filters having different cut-off scales, an input to each successive filter being formed from an output of a previous filter; b) subtracting a current filter output from the previous filter output for said succession of filters to obtain bandpass outputs, known as granularities, consisting of strings of data points which contain strings of zero-valued data points, known as zero segments, and strings of non-zero-valued data points, known as non-zero segments or granules; c) selecting a subset of the granularities; and d) adding together granularities within said subset to produce an output signal containing the granules in said subset so as to preserve sharp signal edges in a smoothed signal.
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Specification