Acoustic signature recognition and identification

A system for recognizing and identifying acoustic signals from a sensor, comprising:

• a pre-Processor for generating a gray-level image of the acoustic signals;
• a feature extractor for detecting, tracking and characterizing at least one line of the gray-level image, said feature extractor calculating a fundamental frequency for each of said at least one line and grouping said at least one line into harmonically related lines based on said fundamental frequency;
• and
• a post-processor for determining a harmonic content of said at least one line and comparing said harmonic content against known acoustic signatures
• wherein said feature extractor includes a line detector for labeling a pixel with a first state and a second state, said first state and said second state being mutually exclusive, wherein said pixel is labeled with said first state if a grey-level value of said pixel is above a first threshold and a KY value of said pixel is above a second threshold;
• and
• wherein said pixel has an upper set of line segments and a lower set of line segments extending radial from said pixel, said line detector further including:
• a first summer for summing grey-level values of all pixels along each of said upper set of line segments and said lower set of line segments, said first summer determining a upper line segment maximum value and a lower line segment maximum value;
• and
• a second summer for summing said upper line segment maximum value and said lower line segment maximum value to determine said KY value.

An apparatus for recognizing and identifying acoustic signals from a sensor, comprising:

• a spectrum analyzer for generating a spectrogram image of the acoustic signals;
• a feature extractor for detecting, tracking and characterizing at least one line of said spectrogram image, said feature extractor calculating a fundamental frequency for each of said at least one line and grouping said at least one line into harmonically related lines based on said fundamental frequency;
• a harmonic set extractor for determining a harmonic content of said at least one line;
• and
• a classifier for comparing said harmonic content against known acoustic signature templates by calculating a weighted score based on said fundamental frequency.

An apparatus for recognizing and identifying acoustic signals from a sensor, comprising:

• a spectrum analyzer for generating a spectrogram image of the acoustic signals;
• a feature extractor for detecting, tracking and characterizing at least one line of said spectrogram image, said feature extractor calculating a fundamental frequency for each of said at least one line and rouping said at least one line into harmonically related lines based on said fundamental frequency;
• a harmonic set extractor for determining a harmonic content of said at least one line;
• and
• a classifier for comparing said harmonic content against known acoustic signature templates
• wherein said feature extractor includes a detector for labeling a pixel with a ON state and a OFF state, wherein said pixel is located with said ON state if a grey-level value of said pixel is above a first threshold and a KY value of said pixel is above a second threshold;
• and
• wherein said pixel has an upper set of line segments and a lower set of line segments extending radial from said pixel, said detector further including:
• a first summer for summing grey-level values of all pixels along each of said upper set of line segments and said lower set of line segments, said first summer determining a upper line segment maximum value and a lower line segment maximum value;
• and
• a second summer for summing said upper line segment maximum value and said lower line segment maximum value to determine said KY value.

A method for recognizing and identifying acoustic signals from a sensor, comprising:

• generating a spectrogram image of the acoustic signals;
• detecting, tracking and characterizing at least one line of said spectrogram image by comparing grey-level values against a first threshold and KY values against a second threshold;
• calculating a fundamental frequency for each of said at least one line;
• grouping said at least one line into harmonically related lines based on said fundamental frequency;
• determining a harmonic content of said at least one line;
• and
• classifying said harmonic content against known acoustic signature templates by calculating a weighted score using said fundamental frequency.

A method for recognizing and identifying acoustic signals from a sensor, comprising:

• generating a spectrogram image of the acoustic signals;
• detecting, tracking and characterizing at least one line of said spectrogram image by comparing grey-level values against a first threshold and KY values against a second threshold;
• calculating a fundamental frequency for each of said at least one line;
• grouping said at least one line into harmonically related lines based on said fundamental frequency;
• determining a harmonic content of said at least one line;
• and
• classifying said harmonic content against known acoustic signature templates
• wherein a pixel has an upper set of line segments and a lower set of line segments extending radial from said pixel, said step of detecting further including the step of:
• summing grey-level values of all pixels along each of said upper set of segments and said lower set of line segments;
• determining a upper line segment maximum value and a lower line segment maximum value;
• and
• summing said upper line segment maximum value and said lower line segment maximum value to determined said KY value.

A method for recognizing and identifying acoustic signals from a sensor, comprising:

• generating a spectrogram image of the acoustic signals;
• detecting, tracking and characterizing at least one line of said spectrogram image by comparing grey-level values against a first threshold and KY values against a second threshold;
• determining a harmonic content of said at least one line;
• classifying said harmonic content against known acoustic signature templates;
• summing grey-level values of all pixels along an upper set of line segments and a lower set of line segments;
• determining an upper line segment maximum value and a lower line segment maximum value;
• and
• summing said upper line segment maximum value and said lower line segment maximum value to determine a KY value.