Shrimp processing system and methods

US9622492B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-9622492-B2
Application numberUS-201515304764-A
CountryUS
Kind codeB2
Filing dateApr 22, 2015
Priority dateApr 24, 2014
Publication dateApr 18, 2017
Grant dateApr 18, 2017

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  1. Title

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  2. Abstract

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  5. First independent claim

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Abstract

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Methods and systems using a vision system to process shrimp. The in-line or off-line vision system captures images of samples of shrimps. The processor produces a digital image of the shrimps in the samples. Shrimps exiting a peeler are imaged to determine the number of tail segments in or the percentage of full weight of each. The shrimps are classified by the number of intact segments, and quality, yield, and throughput computed from the classification results. The processor can control operational settings of the peeler based on the classification results. In a larger system including other shrimp-processing equipment besides the peeler, other points along the processing path can be imaged by camera or sensed by other sensors to determine processing quality and to make automatic operational adjustments to the equipment.

First claim

Opening claim text (preview).

What is claimed is: 1. A shrimp-processing system comprising: a conveyor conveying shrimps along a processing line; an off-line QC station having a vision system capturing digital images of sample shrimps collected from the shrimps on the conveyor; a processor determining the number of tail segments present in each of the sample shrimps or estimating the percentage of full weight of each of the sample shrimps from the digital image and classifying each of the sample shrimps into one of a plurality of classes according to the number of tail segments present in or the percentage of full weight of each of the sample shrimps. 2. A shrimp-processing system as in claim 1 further comprising a shrimp peeling machine removing the heads and shells from the shrimps to produce peeled shrimps from which the sample shrimps are collected. 3. A shrimp-processing system as in claim 1 wherein the off-line QC station further includes a web portal providing remote access. 4. A shrimp-processing system as in claim 1 wherein the off-line QC station further includes one or more sensors detecting one or more operational variables of the processing line or one or more physical characteristics of the sample shrimps and producing sensor signals indicative of the one or more operational variables or physical characteristics. 5. A shrimp-processing system as in claim 4 wherein the one or more sensors include a penetrometer or a texturometer to measure texture, firmness, or soft shell by measuring the force of penetration of the shrimp. 6. A shrimp-processing system as in claim 4 wherein the one or more sensors include an infrared spectrometer to measure moisture content, dehydration, or excessive glazing. 7. A shrimp-processing system as in claim 4 wherein the one or more sensors include a chemosensor or a gas chromatograph to measure shrimp smell. 8. A shrimp-processing system as in claim 4 further including a dryer for drying the sample shrimps and wherein the one or more sensors include a weight sensor that weighs the sample shrimps before and after drying in the dryer. 9. A shrimp-processing system as in claim 4 wherein the one or more sensors are remote from vision system and connected wirelessly or by wire to the off-line QC station. 10. A shrimp-processing system as in claim 1 wherein the vision system includes a source of white light and a source of ultraviolet light and wherein the off-line vision station creates a first digital image of each of the sample shrimps illuminated by white light and a second digital image of each of the sample shrimps illuminated by ultraviolet light. 11. An off-line QC station for a shrimp-processing line, comprising: a vision system capturing a digital image of sample shrimps collected from the shrimps on the conveyor; a processor determining the number of tail segments present in each of the sample shrimps or estimating the percentage of full weight of each of the sample shrimps from the digital image and classifying each of the sample shrimps into one of a plurality of classes according to the number of tail segments present in or the percentage of full weight of each of the sample shrimps. 12. An off-line QC station as in claim 11 wherein the off-line QC station further includes a web portal providing remote access. 13. An off-line QC station as in claim 11 wherein the off-line QC station further includes one or more sensors detecting one or more operational variables of the processing line or one or more physical characteristics of the shrimps and producing sensor signals indicative of the one or more operational variables or physical characteristics. 14. An off-line QC station as in claim 13 wherein the one or more sensors include a penetrometer or a texturometer to measure texture, firmness, or soft shell by measuring the force of penetration of the shrimp. 15. An off-line QC station as in claim 13 wherein the one or more sensors include an infrared spectrometer to measure moisture content, dehydration, or excessive glazing. 16. An off-line QC station as in claim 13 wherein the one or more sensors include a chemosensor or a gas chromatograph to measure shrimp smell. 17. An off-line QC station as in claim 13 further including a dryer for drying the sample shrimps and wherein the one or more sensors include a weight sensor that weighs the sample shrimps before and after drying in the dryer. 18. An off-line QC station as in claim 13 wherein the one or more sensors are remote from vision system and connected wirelessly or by wire to the off-line QC station. 19. An off-line QC station as in claim 11 wherein the vision system includes a source of white light and a source of ultraviolet light and wherein the vision system creates a first digital image of each of the sample shrimps illuminated by white light and a second digital image of each of the sample shrimps illuminated by ultraviolet light. 20. A method for processing shrimps, comprising: transporting shrimps on a conveyor in a conveying direction on a processing line; collecting sample shrimps from the shrimps being transported on the conveyor; creating a digital image of the shrimps in an off-line vision station; determining the number of tail segments in or the percentage of full weight of each of the sample shrimps from the digital image; classifying each of the sample shrimps into one of a plurality of classes according to the number of tail segments present in or the percentage of full weight of each of the shrimps. 21. The method of claim 20 further comprising depositing the sample shrimps onto a support surface so that no shrimp are piggy-backed. 22. The method of claim 20 further comprising detecting one or more operational variables of the processing line or one or more physical characteristics of the shrimps and producing sensor signals indicative of the one or more operational variables or physical characteristics. 23. The method of claim 22 wherein the one or more physical characteristics are one or more of smell, spoilage, black spot, necrosis, soft shell, texture, firmness, dehydration, glazing, unacceptable residual vein, and improperly cut vein. 24. The method of claim 20 comprising creating digital images of each of the shrimps under both white light and ultraviolet light and comparing those images to detect residual shell. 25. The method of claim 20 further comprising weighing the sample shrimps, drying the sample shrimps, weighing the sample shrimps after drying, and comparing the weights before and after drying to determine moisture content of the shrimps.

Assignees

Inventors

Classifications

  • Handling, transporting or packaging pieces of meat · CPC title

  • Beheading shellfish · CPC title

  • Mechanically peeling and shelling shrimps, prawns or other soft-shelled crustaceans · CPC title

  • Grading or classifying shellfish or bivalves · CPC title

  • A22C17/008Primary

    for measuring quality, e.g. to determine further processing · CPC title

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What does patent US9622492B2 cover?
Methods and systems using a vision system to process shrimp. The in-line or off-line vision system captures images of samples of shrimps. The processor produces a digital image of the shrimps in the samples. Shrimps exiting a peeler are imaged to determine the number of tail segments in or the percentage of full weight of each. The shrimps are classified by the number of intact segments, and qu…
Who is the assignee on this patent?
Laitram Llc
What technology area does this patent fall under?
Primary CPC classification A22C17/008. Mapped technology areas include Human Necessities.
When was this patent published?
Publication date Tue Apr 18 2017 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).