초록 ▼

A method for generating a model of a portion of the floor of a body of water from a plurality of depth measurement sources includes determining an overlap of any of the plurality of depth measurement sources with another depth measurement source and generating a relative shift between any two depth

A method for generating a model of a portion of the floor of a body of water from a plurality of depth measurement sources includes determining an overlap of any of the plurality of depth measurement sources with another depth measurement source and generating a relative shift between any two depth measurement sources that overlap. For each depth measurement source that overlaps with at least one other source, generating an overall shift based on the generated relative shifts. The method also includes generating a desired grid having a plurality of grid nodes and generating a model depth at a plurality of the grid nodes based, at least in part, on a global shift for the measurements of the plurality of sources based on the relative shift. Further, an output is generated of all model depths at respective grid nodes.

대표청구항 ▼

A method for generating a model of a portion of the floor of a body of water from a plurality of depth measurement sources includes determining an overlap of any of the plurality of depth measurement sources with another depth measurement source and generating a relative shift between any two depth

A method for generating a model of a portion of the floor of a body of water from a plurality of depth measurement sources includes determining an overlap of any of the plurality of depth measurement sources with another depth measurement source and generating a relative shift between any two depth measurement sources that overlap. For each depth measurement source that overlaps with at least one other source, generating an overall shift based on the generated relative shifts. The method also includes generating a desired grid having a plurality of grid nodes and generating a model depth at a plurality of the grid nodes based, at least in part, on a global shift for the measurements of the plurality of sources based on the relative shift. Further, an output is generated of all model depths at respective grid nodes. rther comprising the step of calibrating the field of vision prior to collecting image data relative to the specimen. 72. The method of claim 71, further comprising the step of obtaining image data reflective of at least one physical dimension of at least a portion of a calibration target. 73. The method of claim 72, wherein the calibration target is substantially similar in size and shape to at least a portion of the specimen. 74. The method of claim 73, further comprising the step of adjusting the field of vision of the image acquisition device by adjusting the position of the image acquisition device. 75. The method of claim 73, wherein the field of vision is adjusted in the x-direction, the y-direction,the z-direction, for pitch, for roll and for yaw. 76. The method of claim 73, wherein the image acquisition device includes a first camera device with a first camera device field of vision and a second camera device with a second camera device field of vision, the method further comprising the step of orienting at least one of the first camera device field of vision and the second camera device field of vision such that the field of vision is directed at a calibration target. 77. The method of claim 76, positioning the first camera device field of vision at 90 degrees with respect to the second camera device field of vision. 78. The method of claim 76, further comprising the step of orienting the first camera device field of vision and the second camera device field of vision such that both fields of vision are directed at a substantially similar area on the calibration target. 79. The method of claim 76, further comprising the step of calibrating the first camera device field of vision with the second camera device field of vision. 80. The method of claim 73, further comprising the steps of: detecting opposite edge locations on a calibration target; and summing pixels between the opposite edge locations in the field of vision. 81. The method of claim 80, further comprising the steps of: repeating the steps of claim 80 for a plurality of opposite edge locations on the calibration target; and calculating an average summation for the pl