Patent Description:
The present invention relates to the field of scanners for differentiating one or more objects detected behind an opaque surface.

As an example, stud finders have been commonly used in construction and home improvement industries. <FIG> illustrates a side view of a conventional scanner. As shown in <FIG>, a scanner <NUM> may be used in a construction and home improvement environment <NUM>. For example, scanner <NUM> may be configured to detect an object <NUM> behind an opaque surface <NUM>. In some exemplary applications, object <NUM> may be a stud, an electrical wire, or a metal pipe. In one exemplary embodiment, the stud may be a wooden stud, vertical wooden element, bridging block, fire block, or any other block, joists, rafters, headers, posts, columns, let brace, or any similar wooden element used for integrity, fabrication, or maintenance of a structural element. In one exemplary embodiment, opaque surface <NUM> may be, for example, a wall covered with drywall, particle board, or plywood; as an example, a floor with opaque material attached to structural members; as an example, a ceiling with an opaque surface, attached to rafters; or any other opaque surface behind which objects are not visible through the surface.

In one exemplary embodiment, scanner <NUM> may include a housing to enclose and protect various electronic components. For example, within the housing of the scanner <NUM>, it may include a printed circuit board (PCB) <NUM>, which can be configured to hold the various electronic components, such as one or more capacitive sensor(s) <NUM>, one or more metal sensors <NUM>, one or more current sensors (not shown), a controller/processor and other integrated circuits (labelled as 106a and 106b). The PCB <NUM> may be coupled to a battery <NUM>, which provides power to the scanner <NUM>. In conventional applications, the one or more capacitive sensor(s) <NUM>, one or more metal sensors <NUM>, and one or more current sensors are typically operated individually or separately. However, such conventional applications may be insufficient to address the complexity of differentiating one or more objects behind the opaque surface <NUM>.

Therefore, there is a need for a scanner that can address the above drawbacks of the conventional scanner in differentiating one or more objects detected behind an opaque surface. Attention is drawn to <CIT> describing a method for locating objects enclosed in a medium, in which a first, high-frequency detection signal is generated by means of at least one capacitive high-frequency sensor, which engages in the medium to be examined, so that information about an object enclosed in the medium is obtained by measuring and evaluating the first detection signal, in particular by measuring the impedance of the capacitive sensor device. It is proposed that at least one further, second detection signal is evaluated to obtain information about the object enclosed in the medium. Further attention is drawn to <CIT> describing a handheld device for locating a foreign body in or beneath a patient's skin comprises one or more sensors that each generate a magnetic or electromagnetic field and a signal reflecting the location and/or size and/or depth of a foreign body and a processor that receives and processes each signal and generates a signal to an operatively connected display. The display that receives the display signal shows the location and/or size and/or depth of the foreign object.

The present invention is set forth in the independent claims. Further embodiments of the invention are described in the dependent claims.

The aforementioned features and advantages of the invention, as well as additional features and advantages thereof, will be more clearly understandable after reading detailed descriptions of embodiments of the invention in conjunction with the non-limiting and non-exhaustive aspects of the following drawings. Like numbers are used throughout the disclosure.

Methods and apparatuses are provided for differentiating one or more objects detected behind an opaque surface. The following descriptions are presented to enable a person skilled in the art to make and use the invention. Descriptions of specific embodiments and applications are provided only as examples. Various modifications and combinations of the examples described herein may be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other examples and applications without departing from the scope of the invention. Thus, the present invention is not intended to be limited to the examples described and shown, but to the appended claims. The word "exemplary" or "example" is used herein to mean "serving as an example, instance, or illustration. " Any aspect or embodiment described herein as "exemplary" or as an "example" is not necessarily to be construed as preferred or advantageous over other aspects or embodiments.

Some portions of the detailed description that follow are presented in terms of flowcharts, logic blocks, and other symbolic representations of operations on information that can be performed on a computer system. A procedure, computer-executed step, logic block, process, etc., is here conceived to be a self-consistent sequence of one or more steps or instructions leading to a desired result. The steps are those utilizing physical manipulations of physical quantities. These quantities can take the form of electrical, magnetic, or radio signals capable of being stored, transferred, combined, compared, and otherwise manipulated in a computer system. These signals may be referred to at times as bits, values, elements, symbols, characters, terms, numbers, or the like. Each step may be performed by hardware, software, firmware, or combinations thereof.

The drawings are presented for illustration purposes, and they are not drawn to scale. In some examples, rectangles, circles or other shapes are used to illustrate shapes of objects and their respective estimated shapes of the objects. In real world applications, the shapes of objects and their respective estimated shapes of the objects may be irregular and may be in any shapes or forms. Note that in the following figures, for each object, a section of the object, not the entire object, is shown. This also applies to the respective estimated shape of each object.

<FIG> illustrates a top view of an exemplary embodiment for differentiating one or more objects detected behind an opaque surface according to aspects of the present invention. As shown in <FIG>, the exemplary embodiment may include a scanner <NUM> an opaque surface <NUM>, and one or more objects (labelled as <NUM>, <NUM>) behind the opaque surface <NUM>. The scanner <NUM> may be configured to differentiate a variety of objects detected behind the opaque surface, including but not limited to, for example: <NUM>) wood studs, wood joists, wood rafters; <NUM>) metallic objects; <NUM>) electrical wires; or <NUM>) other objects. In the example of <FIG>, object <NUM> may be a wood stud, object <NUM> may be a metal pipe, and object <NUM> may be a current source.

<FIG> illustrates a front view of the exemplary embodiment of <FIG> for detecting different objects behind an opaque surface according to aspects of the present invention. In the example of <FIG>, the opaque surface is not shown for simplicity. As shown in <FIG>, the scan direction may be from right to left. A person skilled in the art would understand that the scan direction may be adjusted based on the working environment, the preference of the user, and the specific application. In other words, the scan direction may be from left to right, right to left, up to down, down to up, or diagonally. In some applications, a user may perform multiple scans and/or from multiple directions to improve the accuracy of sensor data collected.

<FIG> illustrates a first set of sensor data collected by the scanner of <FIG> according to aspects of the present invention. In this example, the sensor data may be collected by one or more capacitive sensors of the scanner <NUM>; and one or more items may be included in a set. The signal may represent a change of capacitance due to the change in the density of the objects behind the opaque surface, which may include an indication of the density of object <NUM> and object <NUM>. The vertical axis represents a magnitude of the signal observed by the capacitive sensors, and the horizontal axis represents a distance of the capacitive sensors from the objects being detected. As the scanner <NUM> scans from right to left (as shown in <FIG>), the magnitude of the signal being observed by the capacitive sensors increases, reaching a plateau when the scanner is approximately above the center of the objects. As the scanner <NUM> continues to move pass the center of the objects, the magnitude of the signal being observed by the capacitive sensors decreases.

According to aspects of the present invention, a first reference signal strength (RS<NUM>) may be used to identify the boundaries of object <NUM>. For example, the region between the two dashed lines 210a and 210b has a signal strength at or above RS<NUM>, and this region may be estimated to be where object <NUM> is located. On the other hand, the region outside of the two dashed lines 210a and 210b has a signal strength below RS<NUM>, and this region may be estimated to be where object <NUM> is not found. When the signal magnitude detected by the capacitive sensors reaches the first reference signal strength RS<NUM>, object <NUM> behind the opaque surface may be detected and the boundaries of object <NUM> may be recorded, as indicated by the dashed lines 210a and 210b in <FIG>.

Note that the first reference signal strength RS<NUM> may be derived from empirical experimental data. The first reference signal strength RS<NUM> may be programmable, and may be revised via a software update even after the scanner has been sold, the delivery methods of which are well known to those skilled in the art. At the center of the graph, the distance DMIN1 represent a minimum distance between the capacitive sensors of the scanner <NUM> and the approximate center of the objects. Note that although a right to left scan is described in this example, similar observations may be obtained by a scan from left to right. In some applications, multiple scans from different directions may be used to improve the accuracy of the estimated boundaries of object <NUM>.

<FIG> illustrates a second set of sensor data collected by the scanner of <FIG> according to aspects of the present invention. In the example of <FIG>, the sensor data may be collected by one or more metal sensors of scanner <NUM>; and one or more items may be included in a set. The signal may represent a magnetic field detected behind the opaque surface, primarily affected by the existence of a metal object, such as object <NUM>. The vertical axis represents a magnitude of the signal observed by the metal sensors, and the horizontal axis represents a distance of the metal sensors from object <NUM>. As scanner <NUM> scans from right to left (as shown in <FIG>), the magnitude of the signal being observed by the metal sensors increases, reaching a plateau when the scanner is approximately above the center of object <NUM>. As scanner <NUM> continues to move past the center of object <NUM>, the magnitude of the signal being observed by the metal sensors decreases.

According to aspects of the present invention, a second reference signal strength (RS<NUM>) may be used to identify the boundaries of object <NUM>. For example, the region between the two dashed lines 212a and 212b has a signal strength at or above RS<NUM>, and this region may be estimated to be where object <NUM> is located. On the other hand, the region outside of the two dashed lines 212a and 212b has a signal strength below RS<NUM>, and this region may be estimated to be where object <NUM> is not found. When the signal magnitude detected by the metal sensors reaches the second reference signal strength RS<NUM>, object <NUM> behind the opaque surface may be detected, and the boundaries of object <NUM> may be recorded, as indicated by the dashed lines 212a and 212b in <FIG>.

Note that the second reference signal strength RS<NUM> may be derived from empirical experimental data. The second reference signal strength RS<NUM> may be programmable, and may be revised via a software update even after the scanner <NUM> has been sold, the delivery methods of which are well known to those skilled in the art. At the center of the graph, the distance DMIN2 represents a minimum distance between the metal sensors of scanner <NUM> and the approximate center of object <NUM>. Note that although a right to left scan is described in this example, similar observations may be obtained by a scan from left to right. In some applications, multiple scans from different directions may be used to improve the accuracy of the estimated boundaries of object <NUM>.

<FIG> illustrates a front view of another exemplary embodiment for detecting different objects behind an opaque surface according to aspects of the present invention. As shown in <FIG>, the exemplary embodiment may include a scanner <NUM> and one or more objects (labelled as <NUM> and <NUM>) behind an opaque surface. Note that, for simplicity, the opaque surface is not shown. Object <NUM> may be a wood stud, and object <NUM> may be a metal pipe. The scan direction may be from left to right. The method described above in association with <FIG> may be employed to determine an estimated region for each object behind the opaque surface, which is not repeated here. In this example, rectangle <NUM> represents an estimated region of object <NUM>, and circle <NUM> represents an estimated region of object <NUM>.

<FIG> illustrates an exemplary method of determining an estimated region of an object of <FIG> according to aspects of the present invention. As shown in <FIG>, the method of determining the estimated region of object <NUM> is used as an example. Compared to the actual object <NUM>, a first estimated region 314a can be determined by employing the first reference signal strength (RS<NUM>) as described in association with <FIG>. Since the first reference signal strength may be programmable, for a wood stud, it can be programmed to provide the first estimated region 314a to be smaller than the actual object <NUM>. By choosing the first estimated region 314a to be smaller than the actual object <NUM>, this approach can provide the benefit of having a higher level of confidence that a wood stud is hit when a user drills into the opaque surface.

Additionally or optionally, a second estimated region 314b can be determined by inserting a safety margin. This safety margin is represented by the area between the first estimated region 314a and the second estimated region 314b. Various factors may be used to determine the safety margin, including but not limited to: <NUM>) type of material of the opaque surface; <NUM>) humidity of the environment; <NUM>) temperature of the environment; or <NUM>) other factors that may affect the accuracy of determining the estimated region of object <NUM>. The safety margin may add <NUM>, <NUM>, or other measurements on each side of the first estimated region to form the second estimated region based on the above factors and the design criteria for the scanner. Depending on the application, either the first estimated region 314a or the second estimated region 314b may be used to represent the estimated region of object <NUM>.

<FIG> illustrates another exemplary method of determining an estimated region of another object of <FIG> according to aspects of the present invention. As shown in <FIG>, the method of determining the estimated region of object <NUM> is used as an example. Compared to the actual object <NUM>, a first estimated region 316a can be determined by employing the second reference signal strength (RS<NUM>) as described in association with <FIG>. Since the second reference signal strength may be programmable, for a metal pipe, it can be programmed to provide the first estimated region 316a to be larger than the actual object <NUM>, for example larger by <NUM> millimeter (mm), <NUM>, or other measurements on each side of the first estimated region based on design criteria for the scanner. By choosing the first estimated region 316a to be larger than the actual object <NUM>, this approach can provide the benefit of having a higher level of confidence that a metal object is missed when the user drills into the opaque surface.

Additionally or optionally, a second estimated region 316b can be determined by inserting a safety margin. This safety margin is represented by the area between the first estimated region 316a and the second estimated region 316b. Various factors may be used to determine the safety margin, including but not limited to: <NUM>) type of material of the opaque surface; <NUM>) humidity of the environment; <NUM>) temperature of the environment; or <NUM>) other factors that may affect the accuracy of determining the estimated region of object <NUM>. Depending on the application, either the first estimated region 316a or the second estimated region 316b may be used to represent the estimated region of object <NUM>.

<FIG> illustrates an exemplary implementation of displaying the estimated regions of the different objects of <FIG> according to aspects of the present invention. According to aspects of the present disclosure, a user interface can mean any form of communication to a user, including, but not limited to, visual (for example via a display or one or more light emitting diodes), audible (for example via a speaker) or sensory (for example via a vibration). The information being communicated may be displayed, streamed, stored, mapped, or distributed across multiple devices. Communication to the user can mean either the user or any other person or object which can receive communication. In one approach, when multiple objects are detected, the method determines regions where a single object is detected as well as regions where multiple objects are detected. In the example shown in <FIG>, metal pipe <NUM> may represent a region where multiple objects are detected (for example, which region includes part of stud <NUM>), and rectangle <NUM> (which includes part of metal pipe <NUM>) may represent a region where a part of it has multiple objects (for example, part of metal pipe <NUM> and part of stud <NUM>) and another part of it (excluding the remainder of metal pipe <NUM> and the region that includes both stud <NUM> and metal pipe <NUM>) has a single object.

Based on the above information, for the region of metal pipe <NUM>, the display may be configured to display the multiple objects detected behind the opaque surface for this region. For the region of stud <NUM> that excludes metal pipe <NUM>, the display may be configured to display the single object detected behind the opaque surface. In some implementations, for the region of metal pipe <NUM>, depending on the types of objects detected, such as wood stud and metal pipe in this example, the display may be configured to display nothing for the region of metal pipe <NUM>.

<FIG> illustrates a front view of yet another exemplary embodiment for differentiating one or more objects detected behind an opaque surface according to aspects of the present invention. As shown in <FIG>, the exemplary embodiment may include a scanner <NUM>, and one or more objects (labelled as <NUM> and <NUM>) behind an opaque surface. Note that the opaque surface is not shown for simplicity. Object <NUM> may be a wood stud, and object <NUM> may be an electrical wire. The scan direction may be from left to right. The method described above in association with <FIG> may be employed to determine an estimated region for each object behind the opaque surface, which is not repeated here. In this example, rectangle <NUM> represents an estimated region of object <NUM>, and rectangle <NUM> represents an estimated region of object <NUM>.

<FIG> illustrates an exemplary method of determining an estimated region of an object of <FIG> according to aspects of the present invention. As shown in <FIG>, the method of determining the estimated region of object <NUM> is used as an example. Compared to the actual object <NUM>, a first estimated region 414a can be determined by employing the first reference signal strength (RS<NUM>) as described in association with <FIG>. Since the first reference signal strength may be programmable, for a wood stud, for example, it can be programmed to provide the first estimated region 414a to be smaller than the actual object <NUM>, for example smaller by <NUM>, <NUM>, or other measurements on each side of the first estimated region based on design criteria for the scanner. By choosing the first estimated region 414a to be smaller than the actual object <NUM>, this approach can provide the benefit of having a higher level of confidence that a wood stud is hit when a user drills into the opaque surface.

Additionally or optionally, a second estimated region 414b can be determined by inserting a safety margin. This safety margin is represented by the area between the first estimated region 414a and the second estimated region 414b. Various factors may be used to determine the safety margin, including but not limited to: <NUM>) type of material of the opaque surface; <NUM>) humidity of the environment; <NUM>) temperature of the environment; or <NUM>) other factors that may affect the accuracy of determining the estimated region of object <NUM>. Depending on the application, either the first estimated region 414a or the second estimated region 414b may be used to represent the estimated region of object <NUM>.

<FIG> illustrates another exemplary method of determining an estimated region of another object of <FIG> according to aspects of the present invention. As shown in <FIG>, the method of determining the estimated region of object <NUM> is used as an example. Compared to the actual object <NUM>, a first estimated region 416a can be determined by employing a third reference signal strength (RS<NUM>) similar to the description in association with <FIG>. The third reference signal strength may be programmable. For example, for an electrical wire, it can be programmed to provide the first estimated region 416a to be larger than the actual object <NUM>, for example larger by <NUM>, <NUM>, or other measurements on each side of the first estimated region based on design criteria for the scanner. By choosing the first estimated region 416a to be larger than the actual object <NUM>, this approach can provide the benefit of having a higher level of confidence that an electrical wire is missed when a user drills into the opaque surface.

Additionally or optionally, a second estimated region 416b can be determined by inserting a safety margin. This safety margin is represented by the area between the first estimated region 416a and the second estimated region 416b. Various factors may be used to determine the safety margin, including but not limited to: <NUM>) type of material of the opaque surface; <NUM>) humidity of the environment; <NUM>) temperature of the environment; or <NUM>) other factors that may affect the accuracy of determining the estimated region of object <NUM>. The safety margin may add <NUM>, <NUM>, or other measurements on each side of the first estimated region to form the second estimated region based on the above factors and the design criteria for the scanner. Depending on the application, either the first estimated region 416a or the second estimated region 416b may be used to represent the estimated region of object <NUM>.

<FIG> illustrates an exemplary implementation of displaying the estimated regions of the different objects of <FIG> according to aspects of the present invention. In one approach, when multiple objects are detected, the method determines regions where a single object is detected as well as regions where multiple objects are detected. In the example shown in <FIG>, rectangle <NUM> may represent a region where multiple objects are detected, and rectangle <NUM> (which includes part of rectangle <NUM>) may represent a region where a part of it has multiple objects (for example the region that overlaps with rectangle <NUM>) and another part of it (excluding the region that overlaps with rectangle <NUM>) has a single object.

Based on the above information, for the region of the rectangle <NUM>, the display may be configured to display the multiple objects detected behind the opaque surface for this region. For the region of the rectangle <NUM> that excludes the rectangle <NUM>, the display may be configured to display the single object detected behind the opaque surface. In some implementations, for the region of the rectangle <NUM>, depending on the types of objects detected, such as wood stud and electrical wire in this example, the display may be configured to display nothing for the region of the rectangle <NUM>.

<FIG> illustrates a top view of yet another exemplary embodiment for differentiating one or more objects detected behind an opaque surface according to aspects of the present invention. As shown in <FIG>, the exemplary embodiment may include a scanner <NUM>, an opaque surface <NUM>, and one or more objects (labelled as <NUM>, <NUM>, and <NUM>) behind the opaque surface <NUM>. The scanner <NUM> may be configured to detect a variety of objects behind the opaque surface, including but not limited to: <NUM>) wood studs; <NUM>) metallic objects; <NUM>) electrical wires; or <NUM>) other objects. In the example of <FIG>, object <NUM> may be a wood stud, and object <NUM> may be a metal pipe, and object <NUM> may be an electrical wire.

<FIG> illustrates a front view of the exemplary embodiment of <FIG> for detecting object(s) behind an opaque surface according to aspects of the present invention. In the example of <FIG>, the opaque surface is not shown for simplicity. As shown in <FIG>, the scan direction may be from right to left. A person skilled in the art would understand that the scan direction may be adjusted based on the working environment, the preference of the user, and the specific application. In other words, the scan direction may be from left to right, right to left, up to down, down to up, or diagonally. In some applications, a user may perform multiple scans and/or from multiple directions to improve the accuracy of sensor data collected.

<FIG> illustrates estimated regions of the different objects of <FIG> according to aspects of the present invention. Note that the method of determining an estimated region of an object is described above, for example in association with <FIG>, which is not repeated here. As shown in <FIG>, rectangle <NUM> represents an estimated region for stud <NUM>, rectangle <NUM> represents an estimated region for metal pipe <NUM>, and rectangle <NUM> represents an estimated region for electrical wire <NUM>.

In this particular example, since the object <NUM> is a wood stud, the estimated region <NUM> can be configured to be smaller than stud <NUM>, this approach can provide the benefit of having a higher level of confidence that a wood stud <NUM> is penetrated by a drill bit when a user drills through the opaque surface. Since the object <NUM> is a metal pipe, the estimated region <NUM> can be configured to be larger than metal pipe <NUM>, this approach can provide the benefit of having a higher level of confidence that metal pipe <NUM> is missed when a user drills through the opaque surface. Similarly, since the object <NUM> is an electrical wire, the estimated region <NUM> can be configured to be larger than electrical wire <NUM>, this approach can provide the benefit of having a higher level of confidence that electrical wire <NUM> is missed when a user drills through the opaque surface.

<FIG> illustrates an exemplary implementation of displaying the estimated regions of the different objects of <FIG> according to aspects of the present invention. With the estimated region <NUM> being configured to be smaller than stud <NUM> while the estimated region <NUM> being configured to be larger than metal pipe <NUM>, and the estimated region <NUM> being configured to be larger than electrical wire <NUM>. In some implementations, the display may be configured to display the estimated region for stud <NUM>, represented by rectangle <NUM>, and display the estimated region for metal pipe <NUM>, represented by rectangle <NUM>, and display the estimated region for electrical wire <NUM>, represented by the rectangle <NUM>. In some other implementations, the display may be configured to display the region under the rectangle <NUM> to include both metal pipe <NUM> and wood stud <NUM>, and display the region under the rectangle <NUM> to include both electrical wire <NUM> and wood stud <NUM>.

<FIG> illustrates a top view of an exemplary embodiments for differentiating one or more objects detected behind an opaque surface using sensor data from different sensors according to aspects of the present invention. In the example shown in <FIG>, the exemplary embodiment may include a scanner <NUM>, an opaque surface <NUM>, and one or more objects (labelled as <NUM>) behind the opaque surface <NUM>. In the example of <FIG>, object <NUM> may be, for example, a metal pipe.

<FIG> illustrates a front view of the exemplary embodiment of <FIG> for detecting the object according to aspects of the present invention. In the example of <FIG>, the opaque surface is not shown for simplicity. As shown in <FIG>, the scan direction may be from left to right. A person skilled in the art would understand that the scan direction may be adjusted based on the working environment, the preference of the user, and the specific application. In other words, the scan direction may be from left to right, right to left, up to down, down to up, or diagonally. In some applications, a user may perform multiple scans and/or from multiple directions to improve the accuracy of sensor data collected.

<FIG> illustrates an exemplary method of determining a distance between the scanner and the object of <FIG> according to aspects of the present invention. As shown in <FIG>, the vertical axis represents a common reference point or a common reference line from which a distance between scanner <NUM> and metal pipe <NUM> is estimated. The horizontal axis represents a distance from the common reference point or the common reference line. Scanner <NUM> may to configured to collect sensor data as described above in association with <FIG>. For example, based on the sensor data collected by one or more capacitive sensors of scanner <NUM>, a first distance D<NUM>, representing a distance between scanner <NUM> and metal pipe <NUM>, may be estimated by the capacitive sensors.

In addition, based on the sensor data collected by one or more metal sensors of scanner <NUM>, a second distance D<NUM>, representing a distance between scanner <NUM> and metal pipe <NUM>, may be estimated by the metal sensors. Note that although it is the same object (metal pipe <NUM>) behind opaque surface <NUM>, the capacitive sensors and the metal sensors may provide different estimations with respect to the distance between scanner <NUM> and metal pipe <NUM>. In this exemplary embodiment, due to the presence of a large amount of metal, the metal sensors may provide an estimated distance (e.g. D<NUM>) that is shorter than the actual distance between scanner <NUM> and metal pipe <NUM>. On the other hand, the capacitive sensors may provide an estimated distance (e.g. D<NUM>) that is closer to the actual distance between scanner <NUM> and the metal pipe <NUM>.

From both of the sensor data collected by the capacitive sensors (not shown) and the sensor data collected by the metal sensors (not shown), scanner <NUM> may be configured to derive a distance D<NUM> for metal pipe <NUM> from the common reference. Thus, by using the sensor data collected by the capacitive sensors and the sensor data collected by the metal sensors, scanner <NUM> will obtain an improved estimation of the distance between scanner <NUM> and metal pipe <NUM> in this example. According to aspects of the present invention, both the sensor data collected by the capacitive sensors and the metal sensors may be collected in parallel in a one-pass scan, or multiple sets of sensor data may be collected by the capacitive sensors and the metal sensors in parallel with multiple passes, respectively.

<FIG> illustrates a top view of an exemplary embodiment for differentiating object(s), here a metal screw <NUM> and stud <NUM>, detected behind an opaque surface using sensor data from different sensors according to aspects of the present invention. As shown in <FIG>, the exemplary embodiment may include a scanner <NUM>, an opaque surface <NUM>, and one or more objects (labelled as <NUM> (metal screw) and <NUM> (stud)) behind opaque surface <NUM>. In <FIG>, for example, object <NUM> may be a metal screw and for example, object <NUM> may be a wood stud.

<FIG> illustrates a front view of the exemplary embodiment of <FIG> for detecting the metal object according to aspects of the present invention. As shown in <FIG>, the scan direction may be from left to right. A person skilled in the art would understand that the scan direction may be adjusted based on the working environment, the preference of the user, and the specific application. In other words, the scan direction may be from left to right, right to left, up to down, down to up, or diagonally. In some applications, a user may perform multiple scans and/or from multiple directions to improve the accuracy of sensor data collected.

<FIG> illustrates an exemplary method of determining a distance between the scanner and the metal object of <FIG> (screw <NUM>) according to aspects of the present invention. As shown in <FIG>, the vertical axis represents a common reference point or a common reference line from which a distance between scanner <NUM> and metal screw <NUM> and stud <NUM> is estimated. The horizontal axis represents a distance from the common reference point or the common reference line. Scanner <NUM> may be configured to collect sensor data as described above in association with <FIG>. For example, based on the sensor data collected by one or more capacitive sensors of scanner <NUM>, a first distance D<NUM>, representing a distance between scanner <NUM> and metal screw <NUM> and stud <NUM> may be estimated by the capacitive sensors.

In addition, based on the sensor data collected by one or more metal sensors of scanner <NUM>, a second distance D<NUM>, representing a distance between scanner <NUM> and metal screw <NUM>, may be estimated by the metal sensors. Note that the capacitive sensors and the metal sensors may provide different estimations with respect to the distance between scanner <NUM> and metal screw <NUM> based upon the relative size of the metal screw. In this exemplary embodiment, due to the presence of metal, the metal sensors may provide an estimated distance (e.g. D<NUM>) that is different from the actual distance between scanner <NUM> and metal screw <NUM>. On the other hand, the capacitive sensors may provide an estimated distance (e.g. D<NUM>) that may be closer to the actual distance between scanner <NUM> and metal screw <NUM>.

From both of the sensor data collected by the capacitive sensors and the sensor data collected by the metal sensors, scanner <NUM> may be configured to derive a distance D<NUM> for metal screw <NUM>. Thus, by using the sensor data collected by the capacitive sensors and the sensor data collected by the metal sensors, scanner <NUM> may be able to obtain an improved estimation of the distance between scanner <NUM> and metal screw <NUM> in this example. According to aspects of the present invention, both the sensor data collected by the capacitive sensors and the metal sensors may be collected in parallel in a one-pass scan, or multiple sets of sensor data may be collected by the capacitive sensors and the metal sensors in parallel with multiple passes, respectively.

<FIG> illustrates a block diagram of an exemplary embodiment of a system for differentiating one or more objects detected behind an opaque surface using sensor data from different sensors according to aspects of the present invention. In the exemplary system shown in <FIG>, a controller <NUM> may be configured to process sensor data collected by sensors of the scanner, namely sensor data collected by capacitive sensors <NUM>, metal sensor <NUM>, and current sensor <NUM>. The controller is further configured to determine information about the detected objects behind the opaque surface based on the sensor data collected by capacitive sensors <NUM>, metal sensor <NUM>, and/or current sensor <NUM> in parallel. The controller may include one or more processors. A display <NUM> is configured to provide information about the detected objects to a user.

According to aspects of the disclosure, the functional blocks described in the system of <FIG> may be implemented in an integrated device such as scanner <NUM> of <FIG>. In other implementations, the capacitive sensors <NUM>, metal sensors <NUM>, and current sensor <NUM> may reside in one device, while the controller <NUM> and the display <NUM> may reside in another device. For example, a scanner device may include the sensors, and the sensor data collected by the scanner device may be wirelessly communicated to a second device. The second device, for example a smartphone, a tablet, or a laptop, may include the controller <NUM> and the display <NUM>. In yet other implementations, the controller <NUM>, the capacitive sensors <NUM>, metal sensors <NUM>, and current sensor <NUM>, may reside in one device, while the display <NUM> may reside in another device. For example, a scanner device may include the controller <NUM> and the sensors, and the sensor data collected by the scanner device may be wirelessly communicated to a second device. The second device, for example a monitor, may be configured to receive and display the sensor data.

According to aspects of the present disclosure, examples of capacitive sensors and methods of operating the same are described in <CIT>, entitled "STUD SENSOR WITH OVER-STUD MISCALIBRATION VIA CIRCUIT WHICH STORES AN INITIAL CALIBRATION DENSITY, COMPARES THAT TO A CURRENT TEST DENSITY AND OUTPUTS RESULT VIA INDICATOR. " Examples of metal sensors and methods of operating the same are described in <CIT>, entitled " DUAL ORIENTATION METAL SCANNER. " Examples of current sensors and methods of operating the same are described in <CIT>, entitled " ELECTRICAL CIRCUIT TRACING AND IDENTIFYING APPARATUS AND METHOD," In one exemplary embodiment, current sensors may be alternating current sensors. In another exemplary embodiment, current sensors may be able to detect the static magnetic field of or associated with direct current.

<FIG> illustrates a method of differentiating one or more objects detected behind an opaque surface using sensor data from different sensors according to aspects of the present invention. As shown in <FIG>, in block <NUM>, the method collects, in parallel, sensor data of the one or more objects behind an opaque surface, by a plurality of sensors controlled by one or more processors. In block <NUM>, the method analyzes, by the one or more processors, the sensor data to identify estimated regions of the one or more objects behind the opaque surface. In block <NUM>, the method differentiates, by the one or more processors, the estimated regions of the one or more objects behind the opaque surface. In block <NUM>, the method informs a user, by the one or more processors, of the one or more objects within the estimated regions behind the opaque surface.

According to aspects of the present disclosure, the plurality of sensors may include at least a first set of sensors configured to detect a first type of material and a second set of sensors configured to detect a second type of material; and the estimated regions include a first estimated region of the first type of material and a second estimated region of the second type of material. The first set of sensors may include one or more capacitive sensors and the first type of material include wood studs; and the second set of sensors may include one or more metal sensors and the second type of material include metal objects. The plurality of sensors may further include a third set of sensors configured to detect a third type of material; where the third set of sensors includes one or more current sensors and the third type of material include electrical wires. According to aspects of the present disclosure, a set of sensors may include one or more sensors in the set.

The method of collecting sensor data includes mapping the sensor data of the one or more objects behind the opaque surface with respect to a common reference point. The method of differentiating the estimated regions of the one or more objects behind the opaque surface includes determining an overlap region between the first estimated region and the second estimated region.

<FIG> illustrates a method of analyzing sensor data to identify estimated regions of the objects detected behind an opaque surface according to aspects of the present invention. In the exemplary embodiment of <FIG>, in block <NUM>, the method analyzes the sensor data to identify a first measured region for a wood stud, and reducing the first measured region by a first programmable percentage to derive a first estimated region for the wood stud. In block <NUM>, the method analyzes the sensor data to identify a second measured region for a metal object, and enlarging the second measured region by a second programmable percentage to derive a second estimated region for the metal object.

According to aspects of the present disclosure, the methods performed in block <NUM> and block <NUM> may additionally or optionally include the methods performed in block <NUM> and/or block <NUM>. In block <NUM>, the method analyzes the sensor data to identify a third measured region for an electrical wire, and enlarging the third measured region by a third programmable percentage to derive a third estimated region for the electrical wire. In block <NUM>, the method adds programmable safety margins to the corresponding estimated regions in accordance with variations of an operating environment, where the variations of the operating environment include variations in temperature, humidity, material of the opaque surface, or some combination thereof.

<FIG> illustrates a method of informing a user of the objects detected behind an opaque surface according to aspects of the present invention. In the example shown in <FIG>, the method described in either block <NUM> or block <NUM> may be performed. In block <NUM>, the method prevents display of information in the overlap region. In block <NUM>, the method selectively displays the first type of material, the second type of material, or both types of material in the overlap region.

It will be appreciated that the above descriptions for clarity have described embodiments of the invention with reference to different functional units and controllers.

The invention can be implemented in any suitable form, including hardware, software, firmware, or any combination of these. The invention may optionally be implemented partly as computer software running on one or more data processors and/or digital signal processors, along with the hardware components described above. The elements and components of an embodiment of the invention may be physically, functionally, and logically implemented in any suitable way. Indeed, the functionality may be implemented in a single unit, in a plurality of units, or as part of other functional units. As such, the invention may be implemented in a single unit or may be physically and functionally distributed between different units and processors/controllers.

Claim 1:
A system for differentiating one or more objects detected behind an opaque surface, comprising:
a plurality of sensors (<NUM> ,<NUM>, <NUM>), controlled by one or more processors (<NUM>), configured to collect in parallel, sensor data of the one or more objects behind an opaque surface;
the one or more processors are configured to analyze the sensor data to identify estimated regions of the one or more objects behind the opaque surface;
the one or more processors are further configured to differentiate the estimated regions of the one or more objects behind the opaque surface; and
the one or more processors are further configured to inform a user, via a user interface (<NUM>), of the one or more objects within the estimated regions behind the opaque surface;
characterized in that
the one or more processors are further configured to: analyze the sensor data to identify a first measured region for a wood stud, and reduce the first measured region by a first programmable percentage to derive a first estimated region for the wood stud; and analyze the sensor data to identify a second measured region for a metal object, and enlarge the second measured region by a second programmable percentage to derive a second estimated region for the metal object.