Computational methods for the segmentation of images of objects from background in a flow imaging instrument
First Claim
1. A method for detecting an object in a pixelated image and segmenting the pixelated image to separate the object from a background, comprising the steps of:
- (a) providing pixelated image data for a plurality of pixelated images, where a pixelated image in the plurality of pixelated images may include an object;
(b) detecting the presence of an object included within any of the pixelated images by filtering the pixelated image data, producing filtered image data in which an object is detected in a pixelated image based upon relative amplitude values of pixels corresponding to the filtered image data for said pixelated image;
(c) segmenting the image in which the object was detected by defining a region of interest from the filtered image data for the pixelated image in which the object was detected, so that the region of interest comprises less than all of the filtered image data for said pixelated image, but includes the object that was detected in said pixelated image; and
(d) determining object boundaries for the object using the filtered image data within the region of interest, wherein the step of determining object boundaries comprises the steps of;
(i) applying a first binomial blur operation to the filtered image data within the regions of interest, thereby approximating convolving the filtered image data in the region of interest with a Gaussian filter, producing a Gaussian blurred image data;
(ii) executing a bitwise shift operation on the filtered image data to produce shifted image data;
(iii) determining a difference between the Gaussian blurred image data and the shifted image data to produce difference image data; and
(iv) applying a second binomial blur operation to the difference image data, thereby approximating a Laplacian of the Gaussian (LOG) blurred version of the filtered image data for the region of interest and producing LOG image data.
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Abstract
In automated computation-based interpretation of images, the accuracy and reliability of the detection and delineation of objects, known as “object segmentation,” is implemented so as to provide efficient performance. In a multi-step process, objects are first detected and captured into regions of interest (ROIs). Sets of pixels belonging to respective objects are then identified. Preferably object detection is achieved using both a two-dimensional (2D) low pass filter and a 2D edge enhancement filter. Two different gradient based edge enhancement filters are disclosed. One embodiment of the invention defines a (ROI) by first determining the center of objects by executing a plurality of decimations on the filtered image data, and then establishing object boundaries. In a second embodiment the ROI is defined by generating an amplitude histogram of the filtered image data, and for histograms exceeding a threshold determining by pixel which rows are to be included in the ROI.
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Citations
49 Claims
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1. A method for detecting an object in a pixelated image and segmenting the pixelated image to separate the object from a background, comprising the steps of:
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(a) providing pixelated image data for a plurality of pixelated images, where a pixelated image in the plurality of pixelated images may include an object; (b) detecting the presence of an object included within any of the pixelated images by filtering the pixelated image data, producing filtered image data in which an object is detected in a pixelated image based upon relative amplitude values of pixels corresponding to the filtered image data for said pixelated image; (c) segmenting the image in which the object was detected by defining a region of interest from the filtered image data for the pixelated image in which the object was detected, so that the region of interest comprises less than all of the filtered image data for said pixelated image, but includes the object that was detected in said pixelated image; and (d) determining object boundaries for the object using the filtered image data within the region of interest, wherein the step of determining object boundaries comprises the steps of; (i) applying a first binomial blur operation to the filtered image data within the regions of interest, thereby approximating convolving the filtered image data in the region of interest with a Gaussian filter, producing a Gaussian blurred image data; (ii) executing a bitwise shift operation on the filtered image data to produce shifted image data; (iii) determining a difference between the Gaussian blurred image data and the shifted image data to produce difference image data; and (iv) applying a second binomial blur operation to the difference image data, thereby approximating a Laplacian of the Gaussian (LOG) blurred version of the filtered image data for the region of interest and producing LOG image data. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26)
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27. A method for detecting an object in a pixelated image and segmenting the pixelated image to separate the object from a background, comprising the steps of:
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(a) providing pixelated image data for a plurality of pixelated images, where a pixelated image in the plurality of pixelated images may include an object; (b) detecting the presence of an object included within any of the pixelated images by filtering the pixelated image data, producing filtered image data in which an object is detected in a pixelated image based upon relative amplitude values of pixels corresponding to the filtered image data for said pixelated image, wherein the step of filtering the pixelated image data comprises the steps of; (i) applying a two dimensional low pass filter to the pixelated image data to produce low pass filtered image data; and (ii) applying a two dimensional edge enhancement filter to the low pass filtered image data to produce the filtered image data; (c) segmenting the image in which the object was detected by defining a region of interest from the filtered image data for the pixelated image in which the object was detected, so that the region of interest comprises less than all of the filtered image data for said pixelated image, but includes the object that was detected in said pixelated image, wherein the step of defining a region of interest comprises the steps of; (i) using the filtered image data to generate an amplitude histogram; and (ii) comparing the mean of the amplitude histogram to a threshold value, and if the mean of the amplitude histogram exceeds the threshold value, then analyzing each pixel represented by the filtered image data to determine if the pixel is above the threshold, and if so, then including at least the pixel in the region of interest; and (d) determining object boundaries for the object using the filtered image data within the region of interest. - View Dependent Claims (28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39)
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40. An image signal processing system for detecting an object in an image and segmenting the pixelated image to separate the object from a background, comprising:
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(a) a memory in which a plurality of machine instructions defining a signal processing function are stored; and (b) a processor that is coupled to the memory to access the machine instructions, said processor executing said machine instructions and thereby implementing a plurality of functions, including; (i) detecting the presence of an object included within an pixelated image corresponding to pixelated image data by filtering the pixelated image data, producing filtered image data in which an object is detected in a pixelated image based upon relative amplitude values of pixels corresponding to the filtered image data for said pixelated image; (ii) segmenting the pixelated image in which the object was detected by defining a region of interest from the filtered image data for the pixelated image in which the object was detected, so that the region of interest comprises less than all of the filtered image data for said pixelated image, but includes the object that was detected in said pixelated image; and (iii) determining object boundaries for the object using the filtered image data within the region of interest, wherein the function of determining object boundaries is implemented by; (A) applying a first binomial blur operation to the filtered image data within the regions of interest, thereby approximating convolving the filtered image data in the region of interest with a Gaussian filter, producing a Gaussian blurred image data; (B) executing a bitwise shift operation on the filtered image data to produce shifted image data; (C) determining a difference between the Gaussian blurred image data and the shifted image data to produce difference image data; and (D) applying a second binomial blur operation to the difference image data, thereby approximating a Laplacian of the Gaussian (LOG) blurred version of the filtered image data for the region of interest and producing LOG image data.
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41. An image signal processing system for detecting an object in a pixelated image and segmenting the pixelated image to separate the object from a background, comprising a processor for processing pixilated image data by:
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(a) detecting an object within a pixelated image to which the pixelated image data corresponds, by filtering the pixelated image data, producing filtered image data in which an object is detected in a pixelated image based upon relative amplitude values of pixels corresponding to the filtered image data for said pixelated image, wherein filtering the pixelated image data is implemented by; (i) applying a two dimensional low pass filter to the pixelated image data to produce low pass filtered image data; and (ii) applying a two dimensional edge enhancement filter to the low pass filtered image data to produce the filtered image data; (b) segmenting the pixelated image in which the object was detected by defining a region of interest from the filtered image data for the pixelated image in which the object was detected, so that the region of interest comprises less than all of the filtered image data for said pixelated image, but includes the object that was detected in said pixelated image, wherein defining the region of interest is implemented by; (i) using the filtered image data to generate an amplitude histogram; and (ii) comparing the mean of the amplitude histogram to a threshold value, and if the mean of the amplitude histogram exceeds the threshold value, then analyzing each pixel represented by the filtered image data to determine if the pixel is above the threshold, and if so, then including at least the pixel in the region of interest; and (c) determining object boundaries for the object using the filtered image data within the region of interest. - View Dependent Claims (42, 43)
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44. An article of manufacture adapted for use with a computer, comprising:
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(a) a memory medium; and (b) a plurality of machine instructions, which are stored on the memory medium, said plurality of machine instructions when executed by a computer, causing the computer to; (i) detect an object of interest within a pixelated image by filtering an image data signal; (ii) define a region of interest for the pixelated image, such that the region of interest comprises less than the pixelated image and encompasses the object of interest; and (iii) determine boundaries for objects within the region of interest, wherein the object boundaries are determined by; (A) applying a first binomial blur operation to the filtered image data within the region of interest, thereby approximating convolving the filtered image data in the region of interest with a Gaussian filter, producing a Gaussian blurred image data; (B) executing a bitwise shift operation on the filtered image data to produce shifted image data; (C) determining a difference between the Gaussian blurred image data and the shifted image data to produce difference image data; and (D) applying a second binomial blur operation to the difference image data, thereby approximating a Laplacian of the Gaussian (LOG) blurred version of the filtered image data for the region of interest and producing LOG image data.
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45. An article of manufacture adapted for use with a processor, comprising:
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(a) a memory medium; and (b) a plurality of machine instructions, which are stored on the memory medium, said plurality of machine instructions when executed by a processor, causing the processor to; (i) detect the presence of an object within a pixelated image corresponding to pixelated image data by filtering the pixelated image data, producing filtered image data in which an object is detected in a pixelated image based upon relative amplitude values of pixels corresponding to the filtered image data for said pixelated image; (ii) segment the pixelated image in which the object was detected by defining a region of interest from the filtered image data for the pixelated image in which the object was detected, so that the region of interest comprises less than all of the filtered image data for said pixelated image, but includes the object that was detected in said pixelated image; and (iii) determine object boundaries for the object using the filtered image data within the region of interest, wherein the object boundaries are determined by; (A) approximating convolving the filtered image data in the region of interest with a Gaussian filter, by applying a binomial blur operation to the filtered image data within the region of interest, thereby producing Gaussian blurred image data; (B) approximating a Laplacian of the Gaussian (LOG) blurred version of the filtered image data for the region of interest and producing LOG image data; (C) using the LOG image data to generate a plurality of binary images; (D) manipulating the plurality of binary images to define a binary mask, by dilating at least one of the plurality of binary images, such that at least one of the plurality of binary images remains undilated, and comparing the at least one binary image that was dilated to the at least one binary image that was not dilated to determine a contiguous region associated with the object; and (L) using the binary mask to determine object boundaries.
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46. A method for detecting an object in a pixelated image and segmenting the pixelated image to separate the object from a background, comprising the steps of:
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(a) providing pixelated image data for a plurality of pixelated images, where a pixelated image in the plurality of pixelated images may include an object; (b) detecting the presence of an object included within any of the pixelated images by filtering the pixelated image data, producing filtered image data in which an object is detected in a pixelated image based upon relative amplitude values of pixels corresponding to the filtered image data for said pixelated image; (c) segmenting the image in which the object was detected by defining a region of interest from the filtered image data for the pixelated image in which the object was detected, so that the region of interest comprises less than all of the filtered image data for said pixelated image, but includes the object that was detected in said pixelated image; and (d) determining object boundaries for the object using the filtered image data within the region of interest, wherein the step of determining object boundaries comprises the steps of; (i) approximating convolving the filtered image data in the region of interest with a Gaussian filter, by applying a binomial blur operation to the filtered image data within the region of interest, thereby producing Gaussian blurred image data; (ii) approximating a Laplacian of the Gaussian (LOG) blurred version of the filtered image data for the region of interest and producing corresponding LOG image data; (iii) using the LOG image data to generate a plurality of binary images; (iv) manipulating the plurality of binary images to define a binary mask, by dilating at least one of the plurality of binary images, such that at least one of the plurality of binary images remains undilated, and comparing the at least one binary image that was dilated to the at least one binary image that was not dilated to determine a contiguous region associated with the object; and (v) using the binary mask to determine object boundaries.
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47. An article of manufacture adapted for use with a processor, comprising a memory medium on which are stored a plurality of machine instructions, that when executed by a processor, cause the processor to:
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(a) detect the presence of an object within a pixelated image corresponding to pixelated image data by filtering the pixelated image data, producing filtered image data in which an object is detected in a pixelated image based upon relative amplitude values of pixels corresponding to the filtered image data for said pixelated image, wherein filtering the pixelated image data is implemented by; (i) applying a two dimensional low pass filter to the pixelated image data to produce low pass filtered image data; and (ii) applying a two dimensional edge enhancement filter to the low pass filtered image data to produce the filtered image data; (b) segment the pixelated image in which the object was detected by defining a region of interest from the filtered image data for the pixelated image in which the object was detected, so that the region of interest comprises less than all of the filtered image data for said pixelated image, but includes the object that was detected in said pixelated image, wherein defining the region of interest is implemented by; (i) using the filtered image data to generate an amplitude histogram; and (ii) comparing the mean of the amplitude histogram to a threshold value, and if the mean of the amplitude histogram exceeds the threshold value, then analyzing each pixel represented by the filtered image data to determine if the pixel is above the threshold, and if so, then including at least the pixel in the region of interest; and (c) determine object boundaries for the object using the filtered image data within the region of interest.
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48. An image signal processing system for detecting an object in an image and segmenting the pixelated image to separate the object from a background, comprising:
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(a) a memory in which a plurality of machine instructions defining a signal processing function are stored; and (b) a processor that is coupled to the memory to access the machine instructions, said processor executing said machine instructions and thereby implementing a plurality of functions, including; (i) detecting the presence of an object included within an pixelated image corresponding to pixelated image data by filtering the pixelated image data, producing filtered image data in which an object is detected in a pixelated image based upon relative amplitude values of pixels corresponding to the filtered image data for said pixelated image; (ii) segmenting the pixelated image in which the object was detected by defining a region of interest from the filtered image data for the pixelated image in which the object was detected, so that the region of interest comprises less than all of the filtered image data for said pixelated image, but includes the object that was detected in said pixelated image; and (iii) determining object boundaries for the object using the filtered image data within the region of interest, wherein the object boundaries are determined by; (A) approximating convolving the filtered image data in the region of interest with a Gaussian filter, by applying a binomial blur operation to the filtered image data within the region of interest, thereby producing Gaussian blurred image data; (B) approximating a Laplacian of the Gaussian (LOG) blurred version of the filtered image data for the region of interest and producing LOG image data; (C) using the LOG image data to generate a plurality of binary images; (D) manipulating the plurality of binary images to define a binary mask, by dilating at least one of the plurality of binary images, such that at least one of the plurality of binary images remains undilated, and comparing the at least one binary image that was dilated to the at least one binary image that was not dilated to determine a contiguous region associated with the object; and (E) using the binary mask to determine object boundaries.
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49. A method for detecting an object in a pixelated image and segmenting the pixelated image to separate the object from a background, comprising the steps of:
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(a) providing pixelated image data for a plurality of pixelated images, where a pixelated image in the plurality of pixelated images may include an object; (b) detecting the presence of an object included within any of the pixelated images by filtering the pixelated image data, producing filtered image data in which an object is detected in a pixelated image based upon relative amplitude values of pixels corresponding to the filtered image data for said pixelated image, wherein the step of filtering the pixelated image data comprises the steps of; (i) applying a two dimensional low pass filter to the pixelated image data to produce low pass filtered image data; (ii) applying a two dimensional edge enhancement filter to the low pass filtered image data to produce enhanced image data; and (iii) applying a grayscale manipulation to the enhanced image data, to produce the filtered image data, the filtered image data comprising at least one element selected from the group consisting essentially of a grayscale image and an amplitude histogram; and (c) segmenting the image in which the object was detected by defining a region of interest from the filtered image data for the pixelated image in which the object was detected, so that the region of interest comprises less than all of the filtered image data for said pixelated image, but includes the object that was detected in said pixelated image.
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Specification