Automated rip current detection system

• US 20050271266A1
• Filed: 08/15/2005
• Published: 12/08/2005
• Est. Priority Date: 06/01/2001
• Status: Abandoned Application

• Current Assignee: Gregory Perrier
• Original Assignee: Gregory Perrier
• Inventors: Perrier, Gregory
• Application Number:
  US11/203,771
• Publication Number:
  US 20050271266A1
• Time in Patent Office: Days
• US Class Current: 382/157
• CPC Class Codes: G06F 18/2137 based on criteria of topology preservation, e.g. multidimensional scaling or self-organising maps
• CPC Class Codes: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69

Abstract

A system substitutes digitized images for human vision, in determining the presence or absence of rip tides among sea water wave patterns at a public swimming beach. Computer analysis of these images involves image pre-filtering that enhances the telltale signs of rip tides, before the digital data is processed for classification as NORMAL or RIP TIDE. The classification itself can proceed along by expert systems which mimic the manner in which a human observer performs the detection; or by building a neural network, that determines its own classification criteria for identifying rip tides.

Claims

1. A system for detecting rip tides in the vicinity of a seashore by identifying a number of telltale traits, wherein rip tides strike the shore directly and bounce back sharply as opposed to normal waves which hit the shore obliquely and dissipate their energy before bouncing back, and wherein rip tide waters have different color characteristics than normal seashore waves, and have a different surface texture than normal seashore waves;

said system comprising;

at least one image recorder providing video images;

a computer analyzing said images to detect the presence of rip tides, said analysis involving image pre-filtering enhancing the telltale signs of typical rip tides, and converting said images into digital data processed for classification as NORMAL or RIP TIDE.

2. The system as in claim 1 wherein said at least one image recorder is a camera.

3. The system as in claim 1 wherein said at least one image recorder is a digital camera.

4. The system as in claim 1 wherein said at least one image recorder is a network of satellite image recorders.

5. The system as in claim 1 wherein said at least one image recorder comprises at least one Unmanned Aerial Vehicle.

6. The system as in claim 1 wherein said at least one image recorder comprises at least one watercraft.

7. The system as in claim 1 wherein said at least one image recorder comprises at least one tower mounting device off-shore.

8. The system as in claim 1, wherein the at least one image recorder is a device mounted on a channel marker.

9. The system as in claim 1, wherein the at least one image recorder is a device mounted on a buoy.

10. The system as in claim 1 wherein said computer analysis utilizes expert systems mimicking a manner in which a human observer visually performs rip tide detection, said system codifying rules used by a human;

said system extracting oceanographic visual features of rip tides and determining whether an observed wave pattern is NORMAL OR RIPTIDE.

11. The system as in claim 1 wherein said computer analysis builds a neural network by training said system with many examples of images with known classifications of rip tides, said neural network system determining its own classification criteria, said neural network system distinguishing images of rip tides from normal wave patterns.

12. The system as in claim 1 wherein said system and said at least one image recorder is enclosed within a weather-proof enclosure.

13. The system as in claim 2 wherein said camera includes a wide angle lens.

14. The system as in claim 1 wherein said at least one image recorder is connected via a cable to a computer.

15. The system as in claim 1 wherein said at least one image recorder is wirelessly connected to a computer.

16. The system as in claim 1 wherein said computer is enclosed within a weatherproof enclosure with a transparent glazed display panel and a transparent waterproof flexible cover over a keyboard for inputting data to said computer.

17. The system as in claim 16 wherein said computer accepts external cooling via direct impingement from a fan, which said fan inputs inlet air through a filter and exhausts heated air through at least one exhaust outlet.

18. The system as in claim 1 wherein said system is powered by a power source.

19. The system as in claim 1 further comprising lockable attachment brackets attaching said computer to a life guard perch stand.

20. The system as in claim 1 further comprising a sensory-perceptible alarm warning of the presence of a rip tide.

21. The system as in claim 20 wherein said sensory-perceptible alarm comprises an annunciator module lighting a warning light and an audio amplifier with loudspeaker warning of the presence of a rip tide.

22. The system as in claim 1 wherein said at least one image recorder is a surveillance type video camera.

23. The system as in claim 22 wherein said at least one image recorder is a high resolution megapixel camera, having a native digital interface dispensing with the need for an external frame grabber, said camera connected directly to said computer via an interface.

24. The system as in claim 1 wherein said computer is a laptop computer.

25. The system as in claim 24 wherein said laptop computer has an on/off control over a visual module and provides an audio alarm to an audio amplifier.

26. The system as in claim 10 wherein live video taped images from all input sources of rip tide wave patterns are inputted and classified, said system having predetermined visual clues enabling compilation of classification rules for detecting rip tides, including color or darkness, surface texture, wave patterns, and interactions of these characteristics, said visual characteristics entered into said defined rules;

said system subjecting actual visual images to a number of pre filters to highlight each of said rip tide characteristics, each said filter defining a layer outlining spatially different characteristics;

said system utilizing Fast Fourier Transform (FFT) analysis to create another layer outlining areas of enhanced surface texture, duration and sustainability of said characteristics as well as registration of spatial regions defining said characteristics of an image of a rip tide.

27. The system in claim 26 wherein said computer utilizes a camera frame rate of about three per second.

28. The system in claim 27 wherein said breaks in actual frame sampling are provided to permit said computer to catch up with computations of a series of consecutive frames.

29. The system as in claim 28 wherein said rules are modified and refined over time.

30. The system as in claim 29 wherein a plurality of live video tape snippets are recorded and classified, including a plurality of rip tide as well as a plurality of non rip tide conditions, said system randomly assigning said snippets to a training set and a plurality of test sets, said system configuring along with pre filtering of said video imaging, said neural network being simulated using digital code, said system having a self organizing map (SOM) for identifying rip tide locations.

31. The system as in claim 1 wherein said computer obtains frame images from said at least one image recorder and feeds said frame images into pre filter software, said system utilizing a classification code using new filtered frame data and previously captured frame data to make a determination of the current conditions in the water, and ascertaining whether a riptide been detected, and if not, said system proceeding to acquire a next frame image, and if a rip tide situation has been detected, said system sounding said alarm until a manual reset is detected, and said system having a deployment trigger turning off said alarm and continuing visual surveillance of potential rip tide waters.

32. The system as in claim 1, further comprising a central station linked by a remote data collection entity, that coordinates activities related to rip currents and other hazards at a number of separate beaches in a locality.

33. The system as in claim 1 wherein said system differentiates between hazardous rip currents and non-hazardous currents.

34. The system as in claim 1 wherein said at least one image recorder comprises a plurality of image recorders.

35. The system as in claim 34 wherein said at least one image recorder comprises at least one radar-responsive image recording device.

36. The system as in claim 34 wherein said at least one image recorder comprises at least one infra-red-responsive image recording device.

37. The system as in claim 1 further comprising at least one sensor sensing continuous monitoring of temperature.

38. The system as in claim 1 further comprising at least one sensor sensing continuous monitoring of current velocity.

39. The system as in claim 1 further comprising at least one sensor sensing continuous monitoring of optical backscatter in fixed offshore locations.

40. The system as in claim 1 further comprising at least one multi-channel telemetry receiver to field the remote data streams directly.

41. The system as in claim 1 wherein each image recorder is connected to the central station via a remote communications means.

42. The system as in claim 1 wherein said system moves all data analysis and alarm condition determination to a central master analysis computer.

43. The system as in claim 42, wherein the central master analysis computer combines all input data to determine the current status of a monitored area.

44. The system as in claim 43, wherein the central master analysis computer routes rip current determinations to a life guard stand perch.

45. The system as in claim 44, wherein the central master analysis computer repeats the combination of a new set of gathered input data to maintain constant monitoring of an area.