`Case 1:20-cv-03128—ER Document 1-4 Filed 04/20/20 Page 1 of 7
`
`Exhibit 4
`Exhibit 4
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`
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`Case 1:20-cv-03128-ER Document 1-4 Filed 04/20/20 Page 2 of 7
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`
`Skylum Software’s Luminar 4 - AI Portrait Enhancer
`Infringement of the ‘743 patent
`Claim 1
`1. An automated method for detecting
`red-eye defects in a digital image
`comprising:
`
`
`Evidence
`Skylum Software Luminar 4 performs automated method for detecting red-eye defects in
`a digital image.
`
`For example, the Luminar 4 photo editing software includes an AI Portrait Enhancer
`feature. The AI Portrait Enhancer feature includes a Red Eye function for fixing red eye
`problems caused by a flash.
`
`
`(a) identifying and labeling an image
`segment that includes a potential red-
`eye defect in the image based on a red
`chrominance component and a
`
`[2]
`The AI Portrait Enhancer identifies and labels an image segment that includes a potential
`red-eye defect in the image based on a red chrominance component and a luminance
`component of a color map.
`
`
`
`
`1
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`
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`Case 1:20-cv-03128-ER Document 1-4 Filed 04/20/20 Page 3 of 7
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`luminance component of a color map;
`
`
`For example, the AI Portrait Enhancer includes several smart tools, one of which is the
`Red Eye Removal tool. The Red Eye Removal automatically identifies image segments
`that have potential red-eye defects. This is done based on a red chrominance component
`and a luminance component of a color map for the image. The identified segments would
`necessarily be labelled in some manner, as they could be subject to adjustment based on
`user input from a slider control for the tool.
`
`
` [1]
`
`
`
`
`
`2
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`
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`Case 1:20-cv-03128-ER Document 1-4 Filed 04/20/20 Page 4 of 7
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`(b) eliminating a segment as a candidate
`for having a red-eye defect, said
`eliminating including testing said
`segment and a boundary region of said
`image surrounding said segment for a
`plurality of attributes to determine if
`each said attribute exceeds a pre-
`determined threshold value; and
`
`
`
`The AI Portrait Enhancer eliminates a segment as a candidate for having a red-eye defect,
`said eliminating including testing said segment and a boundary region of said image
`surrounding said segment for a plurality of attributes to determine if each said attribute
`exceeds a pre-determined threshold value.
`
`For example, the Red Eye Removal tool is a smart tool that automatically detects the
`areas of an image that require red eye correction, but leaves other areas of an eye in the
`image untouched. For example, the tool does not affect the redness that is naturally in
`the corner of everyone’s eyes. Therefore, tool must eliminate image segments that were
`candidates for a having a red-eye defect. This elimination would be based on certain
`attributes of regions adjacent to the candidate segment. In the case of redness in the
`corner of an eye, the adjacent region would have attributes such as those consistent with
`a flesh tone. Additionally, size and shape of the candidate segment could also be
`
`
`
`3
`
`
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`Case 1:20-cv-03128-ER Document 1-4 Filed 04/20/20 Page 5 of 7
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`attributes that are considered. Since the tool is a smart tool that works automatically,
`there would be some predetermined threshold value to which the attributes are
`compared to determine if the candidate segment should be eliminated or not.
`
`(c) recording a location, size and
`member pixels of a segment that
`survives said eliminating and is
`confirmed to have a red-eye defect of
`said image.
`
`
` [3]
`
`The AI Portrait Enhancer records a location, size and member pixels of a segment that
`survives said eliminating and is confirmed to have a red-eye defect of said image.
`
`For example, the Red-eye Removal smart tool provides absolute precision to carry out
`red eye correction only on image segments that require it. To do so, the tool would
`necessarily need to record information such as the location, size and member pixels of
`any segments that were candidates for having red-eye defects and that survived the
`elimination process previously described.
`
`
`
`
`
`4
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`
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`Case 1:20-cv-03128-ER Document 1-4 Filed 04/20/20 Page 6 of 7
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` [1]
`
`
`
`
`
`
`References:
`
`[1] Luminar 4: https://skylum.com/luminar-
`2?utm_source=google&utm_medium=cpc&utm_campaign=Luminar_brand_search_en_ca&utm_term=broad&gclid=CjwKCAjwmKLz
`BRBeEiwACCVihpkEFeKn-JvbKYFLtRm9FjqKnEAETd6yOmzuutjHOEC6oLu8hSoDPBoCG6IQAvD_BwE&utm_expid=.jO7k-
`m56RqW2uPJOCHxwmA.1&utm_referrer=https%3A%2F%2Fwww.google.com%2F
`
`[2] Make your portraits shine with Luminar 4: https://community.skylum.com/hc/en-us/community/posts/360050527151-Make-
`your-portraits-shine-with-Luminar-4
`
`
`
`5
`
`
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`Case 1:20-cv-03128-ER Document 1-4 Filed 04/20/20 Page 7 of 7
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`[3] Photofocus: https://photofocus.com/software/three-steps-to-understanding-skin-retouching/
`
`
`
`
`6
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