Digimarc

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Arrangements for digital marking and reading of items, useful in recycling

Abstract
Images depicting items in a waste flow on a conveyor belt are provided to two analysis systems. The first system processes images to decode digital watermark payload data found on certain of the items (e.g., plastic containers). This payload data is used to look up corresponding attribute metadata for the items in a database, such as the type of plastic in each item, and whether the item was used as a food container or not. The second analysis system can be a spectroscopy system that determines the type of plastic in each item by its absorption characteristics. When the two systems conflict in identifying the plastic type, a sorting logic processor applies a rule set to arbitrate the conflict and determine which plastic type is most likely. The item is then sorted into one of several different bins depending on a combination of the final plastic identification, and whether the item was used as a food container or not. A variety of other features and arrangements are also detailed.



Digital marking of items for recycling

Abstract
A plastic item, such as a beverage bottle, can convey two distinct digital watermarks, encoded using two distinct signaling protocols. A first, printed label watermark conveys a retailing payload, including a Global Trade Item Number (GTIN) used by a point-of-sale scanner in a retail store to identify and price the item when presented for checkout. A second, plastic texture watermark may convey a recycling payload, including data identifying the composition of the plastic. The use of two different signaling protocols assures that a point-of-sale scanner will not spend its limited time and computational resources working to decode the recycling watermark, which may lack data needed for retail checkout. In some embodiments, a recycling apparatus makes advantageous use of both types of watermarks to identify the plastic composition of the item (e.g., relating GTIN to plastic type using an associated database), thereby increasing the fraction of items that are correctly identified for sorting and recycling. In other embodiments the plastic item (or a label thereon) bears only a single watermark. A great number of other features and arrangements are also detailed.



Signaling arrangements employing molded thermoplastics

Abstract
A thermoplastic resin, such as PET, is molded to define a 2D code signal, such as a digital watermark pattern. The mold can comprise an array of hole or spike features, some of which are directly vented to atmospheric pressure. A network of channels can link the other features to the directly-vented features, so all features are vented. A mold comprising spike features can form a digital watermark pattern on an item such that the watermark payload is decodable both from the side of the item that contacted the mold, and also from the opposite, non-contact side of the item. To aid entry of viscous thermoplastic among the very fine elemental features of a mold representing a watermark signal pattern, the features can be overlapped, forming a connected binary mark having larger features. A variety of other improvements and arrangements are also detailed.



Laser marking of machine-readable codes

Abstract
A surface is laser-etched to convey a 2D machine-readable code pattern. Various strategies are detailed to minimize the etching time. Some strategies include modifying the code pattern to reduce a path length traveled by the laser. Some strategies include modifying the code pattern to make it sub-optimal, i.e., making the code pattern a less-faithful approximation of an ideal code pattern. In some embodiments the etched surface is the surface of a plastic container, and the code pattern conveys information indicating the type of plastic of which the container is manufactured. A variety of other features and arrangements are also detailed.


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The above patents reference BrainChip's Akida:

Still another type of processor hardware is a neural network chip, e.g., the Intel Nervana NNP-T, NNP-I and Loihi chips, the Google Edge TPU chip, and the Brainchip Akida neuromorphic SOC.
 
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