MACHINE VISION BASED OBSTACLE AVOIDANCE SYSTEM
First Claim
Patent Images
1. A method of detecting an obstacle in a field of view of a mobile platform having a base structure, a drive mechanism and a machine vision system, comprising:
- capturing an image in the form of a signal;
converting the signal into a digital image having a plurality of pixels and inverting the digital image;
normalizing the digital image by setting pixels in the plurality of pixels having an intensity value away from a histogram global maximum to a first predetermined intensity and setting pixels in the plurality of pixels having intensity values close to the global maximum to a second predetermined intensity;
performing edge detection on the normalized digital image, thereby outputting a bounding graph indicating edges of detected objects in the image; and
determining local maximums and zeros in the graph, and determining a dynamic mask based on said maximums and zeros, wherein the dynamic mask is applied to a second digital image to determine the presence of an object, wherein pixels having intensity value away from the global maximum of the histogram are assigned a first intensity value I1, and pixels which have intensity values close to the global maximum, are assigned a second intensity value I2.
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Abstract
Machine vision based obstacle avoidance system is provided. The system utilizes a CCD camera to capture an image. A normalized image and dynamic masking is used in object detection
21 Citations
20 Claims
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1. A method of detecting an obstacle in a field of view of a mobile platform having a base structure, a drive mechanism and a machine vision system, comprising:
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capturing an image in the form of a signal; converting the signal into a digital image having a plurality of pixels and inverting the digital image; normalizing the digital image by setting pixels in the plurality of pixels having an intensity value away from a histogram global maximum to a first predetermined intensity and setting pixels in the plurality of pixels having intensity values close to the global maximum to a second predetermined intensity; performing edge detection on the normalized digital image, thereby outputting a bounding graph indicating edges of detected objects in the image; and determining local maximums and zeros in the graph, and determining a dynamic mask based on said maximums and zeros, wherein the dynamic mask is applied to a second digital image to determine the presence of an object, wherein pixels having intensity value away from the global maximum of the histogram are assigned a first intensity value I1, and pixels which have intensity values close to the global maximum, are assigned a second intensity value I2. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A mobile platform comprising:
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a base structure; a drive mechanism coupled to the base structure; a machine vision system including an optical input module that captures an image in the form of a signal; a pre-processing module that receives said signal from the optical input module, that converts the signal into a digital image having a plurality of pixels and that inverts the digital image; an image normalizing module that normalizes the digital image by setting pixels in the plurality of pixels having an intensity less than a predetermined threshold to a first predetermined intensity and setting pixels in the plurality of pixels having an intensity greater than or equal to the predetermined threshold to a second predetermined intensity; an edge detection module that receives the normalized digital image and performs edge detection the normalized digital image, thereby outputting a bounding graph indicating edges of detected objects in the image; and a detection module that receives the bounding graph and determines local maximums and zeros in the graph, and determines a dynamic mask based on said maximums and zeros, wherein the dynamic mask is applied to a second digital image to determine the presence of an object. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18, 19)
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20. A mobile platform comprising:
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a base structure that is one of a motorized wheel chair, a wheel chair, a robotic cleaner, a robotic vacuum, and a cane; a drive mechanism coupled to the base structure; a machine vision system including; an optical input module that captures an image in the form of a signal; a pre-processing module that receives said signal from the optical input module, that converts the signal into a grayscale digital image having a plurality of pixels and that inverts the digital image; an image normalizing module that normalizes the digital image by setting pixels in the plurality of pixels having an intensity less than a predetermined threshold to a first predetermined intensity and setting pixels in the plurality of pixels having an intensity greater than or equal to the predetermined threshold to a second predetermined intensity; an edge detection module that receives the normalized digital image and performs edge detection the normalized digital image, thereby outputting a bounding graph indicating edges of detected objects in the image; an image filtering module that receives the bounding graph from the edge detection module and filters noise peaks in the bounding graph; a clipping module that receives the filtered bounding graph from the image filtering module and removes a portion of the filtered bounding graph corresponding to additional noise in the filtered bounding graph and replaces said removed portion with a smoothed portion; a detection module that receives the clipped and filtered bounding graph and determines local maximums and zeros in the graph, and determines a dynamic mask based on said maximums and zeros, wherein the dynamic mask is applied to a second digital image to determine the presence of an object; and an object detection module that partitions the second digital image into a plurality of sections and determines a location of the object by determining a section of the plurality of sections having the dynamic mask located therein.
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Specification