Abstract: The present disclosure provides a high resolution structured light system that is also capable of maintaining high throughput. The high resolution structured light system includes one or more image capture devices, such as a camera and/or an image sensor, a projector, and a blurring element. The projector is configured to project a binary pattern so that the projector can operate at high throughput. The binary projection pattern is subsequently filtered by the blurring element to remove high frequency components of the binary projection pattern. This filtering smoothes out sharp edges of the binary projection pattern, thereby creating a blurred projection pattern that changes gradually from the low value to the high value. This gradual change can be used by the structured light system to resolve spatial changes in the 3D profile that could not otherwise be resolved using a binary pattern.

Abstract: The present disclosure provides a high resolution structured light system that is also capable of maintaining high throughput. The high resolution structured light system includes one or more image capture devices, such as a camera and/or an image sensor, a projector, and a blurring element. The projector is configured to project a binary pattern so that the projector can operate at high throughput. The binary projection pattern is subsequently filtered by the blurring element to remove high frequency components of the binary projection pattern. This filtering smoothes out sharp edges of the binary projection pattern, thereby creating a blurred projection pattern that changes gradually from the low value to the high value. This gradual change can be used by the structured light system to resolve spatial changes in the 3D profile that could not otherwise be resolved using a binary pattern.

Abstract: The present disclosure provides a high resolution structured light system that is also capable of maintaining high throughput. The high resolution structured light system includes one or more image capture devices, such as a camera and/or an image sensor, a projector, and a blurring element. The projector is configured to project a binary pattern so that the projector can operate at high throughput. The binary projection pattern is subsequently filtered by the blurring element to remove high frequency components of the binary projection pattern. This filtering smoothes out sharp edges of the binary projection pattern, thereby creating a blurred projection pattern that changes gradually from the low value to the high value. This gradual change can be used by the structured light system to resolve spatial changes in the 3D profile that could not otherwise be resolved using a binary pattern.

Abstract: The present disclosure provides a high resolution structured light system that is also capable of maintaining high throughput. The high resolution structured light system includes one or more image capture devices, such as a camera and/or an image sensor, a projector, and a blurring element. The projector is configured to project a binary pattern so that the projector can operate at high throughput. The binary projection pattern is subsequently filtered by the blurring element to remove high frequency components of the binary projection pattern. This filtering smoothes out sharp edges of the binary projection pattern, thereby creating a blurred projection pattern that changes gradually from the low value to the high value. This gradual change can be used by the structured light system to resolve spatial changes in the 3D profile that could not otherwise be resolved using a binary pattern.

Abstract: The disclosed apparatus, systems, and methods provide for a displacement sensor with a multi-position image sensor. The displacement sensor includes an optical lens. The displacement sensor includes an image sensor configured to view an object through the lens along a plane of focus that is not parallel to an image plane of the image sensor. The displacement sensor includes a laser for illuminating the object by the displacement sensor, wherein the laser is: spaced from the lens at a fixed distance, and configured to project a line of light along the plane of focus of the image sensor. The displacement sensor comprises a first configuration wherein the image sensor is at a first location along an image plane with a first field of view along the plane of focus, and a second configuration at a second location with a different field of view.

Abstract: A method and system for specifying an area of interest in a 3D imaging system including a plurality of cameras that include at least first and second cameras wherein each camera has a field of view arranged along a camera distinct trajectory, the method comprising the steps of presenting a part at a location within the fields of view of the plurality of cameras, indicating on the part an area of interest that is within the field of view of each of the plurality of cameras, for each of the plurality of cameras: (i) acquiring at least one image of the part including the area of interest, (ii) identifying a camera specific field of interest within the field of view of the camera associated with the area of interest in the at least one image and (iii) storing the field of interest for subsequent use.

Abstract: The disclosed apparatus, systems, and methods provide for a displacement sensor with a multi-position image sensor. The displacement sensor includes an optical lens. The displacement sensor includes an image sensor configured to view an object through the lens along a plane of focus that is not parallel to an image plane of the image sensor. The displacement sensor includes a laser for illuminating the object by the displacement sensor, wherein the laser is: spaced from the lens at a fixed distance, and configured to project a line of light along the plane of focus of the image sensor. The displacement sensor comprises a first configuration wherein the image sensor is at a first location along an image plane with a first field of view along the plane of focus, and a second configuration at a second location with a different field of view.

Abstract: A method for training a pattern recognition algorithm including the steps of identifying the known location of the pattern that includes repeating elements within a fine resolution image, using the fine resolution image to train a model associated with the fine image, using the model to examine the fine image resolution image to generate a score space, examining the score space to identify a repeating pattern frequency, using a coarse image that is coarser than the finest image resolution image to train a model associated with the coarse image, using the model associated with the coarse image to examine the coarse image thereby generating a location error, comparing the location error to the repeating pattern frequency and determining if the coarse image resolution is suitable for locating the pattern within a fraction of one pitch of the repeating elements.

Abstract: An apparatus and method are disclosed for setting up a vision system having a camera and a vision processor cooperative with the camera. The apparatus includes a gesture recognizer, a key recognizer, a breakout box having at least two signaling elements, and a setup control unit that is cooperative with the gesture recognizer, the key recognizer, and the breakout box. The combination of using a key and a gesture set as herein described is substantially superior, as compared with known user interfaces for setting up a vision system that has been previously been engineered, in terms of low-cost, convenience, ease-of-use, simplicity, and speed.

Abstract: A method for training a pattern recognition algorithm including the steps of identifying the known location of the pattern that includes repeating elements within a fine resolution image, using the fine resolution image to train a model associated with the fine image, using the model to examine the fine image resolution image to generate a score space, examining the score space to identify a repeating pattern frequency, using a coarse image that is coarser than the finest image resolution image to train a model associated with the coarse image, using the model associated with the coarse image to examine the coarse image thereby generating a location error, comparing the location error to the repeating pattern frequency and determining if the coarse image resolution is suitable for locating the pattern within a fraction of one pitch of the repeating elements.

Abstract: A method for training a pattern recognition algorithm for a machine vision system that uses models of a pattern to be located, the method comprising the steps of training each of a plurality of models using a different training image wherein each of the training images is a version of a single image of the pattern at a unique coarse image resolution, using the models to identify at least one robust image resolution where the image resolution is suitable for locating the pattern within an accuracy limit of the actual location of the pattern in the image and storing the at least one robust image resolution for use in subsequent pattern recognition processes.

Abstract: A method for automatically determining machine vision tool parameters is presented, including: marking to indicate a desired image result for each image of a plurality of images; selecting a combination of machine vision tool parameters, and running the machine vision tool on the plurality of images using the combination of parameters to provide a computed image result for each image of the plurality of images, each computed image result including a plurality of computed measures; comparing each desired image result with a corresponding computed image result to provide a comparison result vector associated with the combination of machine vision tool parameters, then comparing the comparison result vector associated with the combination of machine vision tool parameters to a previously computed comparison result vector associated with a previous combination of machine vision tool parameters using a result comparison heuristic to determine which combination of machine vision tool parameters is best overall.

Abstract: A method for automatically determining machine vision tool parameters is presented, including: marking to indicate a desired image result for each image of a plurality of images; selecting a combination of machine vision tool parameters, and running the machine vision tool on the plurality of images using the combination of parameters to provide a computed image result for each image of the plurality of images, each computed image result including a plurality of computed measures; comparing each desired image result with a corresponding computed image result to provide a comparison result vector associated with the combination of machine vision tool parameters, then comparing the comparison result vector associated with the combination of machine vision tool parameters to a previously computed comparison result vector associated with a previous combination of machine vision tool parameters using a result comparison heuristic to determine which combination of machine vision tool parameters is best overall.

Abstract: An apparatus and method are disclosed for setting up a vision system having a camera and a vision processor cooperative with the camera. The apparatus includes a gesture recognizer, a key recognizer, a breakout box having at least two signaling elements, and a setup control unit that is cooperative with the gesture recognizer, the key recognizer, and the breakout box. The combination of using a key and a gesture set as herein described is substantially superior, as compared with known user interfaces for setting up a vision system that has been previously been engineered, in terms of low-cost, convenience, ease-of-use, simplicity, and speed.

Abstract: An apparatus and method are disclosed for setting up a vision system having a camera and a vision processor cooperative with the camera. The apparatus includes a gesture recognizer, a key recognizer, a breakout box having at least two signaling elements, and a setup control unit that is cooperative with the gesture recognizer, the key recognizer, and the breakout box. The combination of using a key and a gesture set as herein described is substantially superior, as compared with known user interfaces for setting up a vision system that has been previously been engineered, in terms of low-cost, convenience, ease-of-use, simplicity, and speed.

Abstract: Digital image processing methods are applied to an image of a semiconductor interconnection pad to preprocess the image prior to an inspection or registration. An image of a semiconductor pads exhibiting spatial patterns from structure, texture or features are filtered without affecting features in the image not associated with structure or texture. The filtered image is inspected in a probe mark inspection operation.

Abstract: A method and system for specifying an area of interest in a 3D imaging system including a plurality of cameras that include at least first and second cameras wherein each camera has a field of view arranged along a camera distinct trajectory, the method comprising the steps of presenting a part at a location within the fields of view of the plurality of cameras, indicating on the part an area of interest that is within the field of view of each of the plurality of cameras, for each of the plurality of cameras: (i) acquiring at least one image of the part including the area of interest, (ii) identifying a camera specific field of interest within the field of view of the camera associated with the area of interest in the at least one image and (iii) storing the field of interest for subsequent use.

Abstract: An image of a semiconductor interconnection pad is analyzed to determine a geometric description of the zone regions of a multiple zone semiconductor interconnection pad. Edge detection machine vision tools are used to extract features in the image. The extracted features are analyzed to derive geometric descriptions of the zone regions of the pad, that are applied in semiconductor device inspection, fabrication, and assembly operations.

Abstract: Digital image processing methods are applied to an image of a semiconductor interconnection pad to preprocess the image prior to an inspection or registration. An image of a semiconductor pads exhibiting spatial patterns from structure, texture or features are filtered without affecting features in the image not associated with structure or texture. The filtered image is inspected in a probe mark inspection operation.

Abstract: The invention provides inter alia methods and apparatus for determining the pose, e.g., position along x-, y- and z-axes, pitch, roll and yaw (or one or more characteristics of that pose) of an object in three dimensions by triangulation of data gleaned from multiple images of the object. Thus, for example, in one aspect, the invention provides a method for 3D machine vision in which, during a calibration step, multiple cameras disposed to acquire images of the object from different respective viewpoints are calibrated to discern a mapping function that identifies rays in 3D space emanating from each respective camera's lens that correspond to pixel locations in that camera's field of view. In a training step, functionality associated with the cameras is trained to recognize expected patterns in images to be acquired of the object.