Adaptive vision system
First Claim
1. A method of identifying at least one valid object having at least one predetermined attribute value in a background, comprising the steps of:
- (a) generating an image of the object and the background;
(b) generating a gray level histogram of the image, the gray level histogram having an entropy function;
(c) entropically selecting a threshold gray level such that the entropy function of the histogram is maximized;
(d) searching the image using the entropically selected threshold gray level for at least one candidate object, wherein the candidate object has at least one candidate object attribute value;
(e) validating the candidate object having the valid object predetermined attribute value to identify [the]a valid object;
(f) subdividing the gray level histogram into an upper histogram and a lower histogram using the entropic threshold gray level as defined by step (c) as an upper delimiter and a lower delimiter; and
(g) recursively repeating steps (c)-(f) for each of the upper and lower histograms, wherein the repetition of step (c) selects a next successive entropic threshold gray level, thereby recursively partitioning the gray level histogram until a predetermined minimum number of new valid objects is identified.
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Abstract
The present invention relates to image analysis methods and systems for identifying objects in a background by generating a description, which may be either a histogram or co-occurrence matrix, of the gray level space of the image by using an entropic kernel to recursively analyze the gray level space for candidate objects and validating the presence of valid objects by comparing the candidate object attribute values to a defined set of valid object attribute values contained in a driver. The present invention includes recursive, iterative and parallel processing methods. The methods may be used in a wide variety of industrial inspection techniques, including colony counting and the identification of discrete features in carpets and of pigment elements embedded in a polymer.
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Citations
64 Claims
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1. A method of identifying at least one valid object having at least one predetermined attribute value in a background, comprising the steps of:
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(a) generating an image of the object and the background; (b) generating a gray level histogram of the image, the gray level histogram having an entropy function; (c) entropically selecting a threshold gray level such that the entropy function of the histogram is maximized; (d) searching the image using the entropically selected threshold gray level for at least one candidate object, wherein the candidate object has at least one candidate object attribute value; (e) validating the candidate object having the valid object predetermined attribute value to identify [the]a valid object; (f) subdividing the gray level histogram into an upper histogram and a lower histogram using the entropic threshold gray level as defined by step (c) as an upper delimiter and a lower delimiter; and (g) recursively repeating steps (c)-(f) for each of the upper and lower histograms, wherein the repetition of step (c) selects a next successive entropic threshold gray level, thereby recursively partitioning the gray level histogram until a predetermined minimum number of new valid objects is identified. - View Dependent Claims (3, 4, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48)
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2. A method of identifying at least one valid discrete feature in a carpet, the discrete feature having at least one valid feature predetermined attribute value, comprising the steps of:
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(a) generating an image of the feature and the carpet; (b) generating a gray level histogram of the image, the gray level histogram having an entropy function; (c) entropically selecting a threshold gray level such that the entropy function of the histogram is maximized; (d) searching the image using the entropically selected threshold gray level for at least one candidate feature, wherein the candidate feature has at least one candidate feature attribute value; (e) validating the candidate feature having the valid feature predetermined attribute value to identify a valid feature; (f) subdividing the gray level histogram into an upper histogram and a lower histogram using the entropically selected threshold gray level as defined in step (c) as an upper delimiter and a lower delimiter; and (g) recursively repeating steps (c)-(f) for each of the upper and lower histograms, wherein the repetition of step (c) selects a next successive entropic threshold gray level, thereby recursively partitioning the gray level histogram until a predetermined minimum number of new valid features is identified. - View Dependent Claims (6)
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5. A method of identifying at least one valid pigment element embedded in a polymer, the pigment element having at least one valid pigment element predetermined attribute value, comprising the steps of:
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(a) generating an image of the pigment element and the polymer; (b) generating a gray level histogram of the image, the gray level histogram having an entropy function; (c) entropically selecting a threshold gray level such that the entropy function of the histogram is maximized; (d) searching the image using the entropically selected threshold gray level for at least one candidate pigment element, wherein the candidate pigment element has at least one candidate pigment element attribute value; (e) validating the candidate pigment element having the valid pigment element predetermined attribute value to identify a valid pigment element; (f) subdividing the gray level histogram into an upper histogram and a lower histogram using the entropically selected threshold gray level as defined in step (c) as an upper delimiter and a lower delimiter; and (g) recursively repeating steps (c)-(f) for each of the upper and lower histograms, wherein the repetition of step (c) selects a next successive entropic threshold gray level, thereby recursively partitioning the gray level histogram until a predetermined minimum number of new valid elements is identified.
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49. The method as claimed in 45 or 47, further including the step of tracing the clump in a singular color indicative of the number of valid objects in the candidate clump.
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50. The method as claimed in 46 or 48, further including the step of tracing the clump in a color plurality of colors indicative of the number of valid objects in the candidate clump, wherein all the points of the perimeter of the clump of valid objects between the adjacent valleys on the distance buffer are traced in the same color.
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51. A system for identifying at least one valid object having at least one predetermined attribute value in a background, comprising:
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(a) means for generating an image of the object and the background; and (b) computer means including; (i) a driver for storing the definition of the valid object, and (ii) an entropic kernel for; (A) generating a gray level histogram of the image, (B) entropically selecting a threshold gray level such that the entropy function of the histogram is maximized, (C) searching the image using the entropically selected threshold gray level for at least one candidate object, wherein the candidate object has at least one candidate object attribute value, (D) validating the candidate object having the valid object predetermined attribute value to identify a valid object, (E) subdividing the gray level histogram into an upper histogram and a lower histogram using the entropic threshold gray level as defined by step (B) as an upper delimiter and a lower delimiter, and (F) recursively repeating steps (B)-(E) for each of the upper and lower histograms, wherein the repetition of step (B) selects a next successive entropic threshold gray level, thereby recursively partitioning the gray level histogram until a predetermined minimum number of new valid objects is identified. - View Dependent Claims (52, 53, 54, 55)
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56. A method of counting at least one valid biological colony having at least one predetermined attribute value in a background, comprising the steps of:
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(a) generating an image of the colony and the background; (b) generating a gray level histogram of the image, the gray level histogram having an entropy function; (c) entropically selecting a threshold gray level such that the entropy function of the histogram is maximized; (d) searching the image using the entropically selected threshold gray level for at least one candidate colony, wherein the candidate colony has at least one candidate colony attribute value; (e) validating the candidate colony having the valid colony predetermined attribute value to identify a valid colony; (f) subdividing the gray level histogram into an upper histogram and a lower histogram using the entropically selected threshold gray level as defined in step (c) as an upper delimiter and a lower delimiter; and (g) recursively repeating steps (c)-(f) for each of the upper and lower histograms, wherein the repetition of step (c) selects a next successive entropic threshold gray level, thereby recursively partitioning the gray level histogram until a predetermined minimum number of new valid colonies is counted. - View Dependent Claims (57, 58, 59, 60, 61, 62, 63)
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64. A method of identifying at least one valid object having at least one predetermined attribute value in a background, comprising the steps of:
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(a) generating an image of the object and the background; (b) generating a histogram representative of the entire image, the gray level histogram having an entropy function; (c) generating a plurality of gray level upper and lower histograms of the image from the histogram, each gray level upper and lower histogram having a respective entropy function; (d) automatically selecting a threshold gray level value for each upper and lower histogram such that the entropy function of each histogram is maximized; (e) searching the image using the automatically selected threshold gray level value for each upper and lower histogram for at least one candidate object, wherein the candidate object has at least one candidate object attribute value; and (f) validating the candidate object having the valid object predetermined attribute value to identify the valid object.
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Specification