Metrologic Instruments, Inc.

Hand Held Products, Inc.

Other

Honeywell International Inc.

David M Wilz

George B Rockstein

Carl Harry Knowles

Ka Man Au

C Harry Knowles

Patrick Anthony Giordano

Robert E Blake

Stephen J Colavito

Xiaoxun Zhu

Mark C Schmidt

Garrett K Russell

Michael Vincent Miraglia

Donald T Hudrick

Christopher Allen

Thomas A Amundsen

Taylor Smith

Anatoly Kotlarsky

Sudhin Mandal

Shawn De Foney

Jie Ren

Gennady Germaine

Weizhen Yan

Timothy A Good

Michael L Veksland

Charles A Naylor

George Kolis

David P Bubnoski

Benjamin Hejl

LeRoy Dickson

Sankar Ghosh

Sung Byun

Ian A Scott

Andrew D Dehennis

Erik Van Horn

John Bonanno

Lin Wang

Congwei Xu

Min Jiang

Meng Hu

Hongjian Jin

MingQing Ji

Shamei Shi

James C Nahill

Gene German

Tao Xian

Michael Schnee

John A Furlong

Shane Michael Edmonds

Sergio Movsessian

William Martin

Jeffrey Dean Harper

Kevin DiPlacido

Constantine J Tsikos

John Groot

Thomas Merritt Haggerty

Mikhail L Veksland

Thomas A Sweet

Francis E Lodge

Ynjiun P Wang

Yong Liu

Mark Hernandez

Duane Ellis

Timothy Williams

Dwight Linwood Franz

Shawn Defoney

HongJian Jin

Kevin Saber

James A Cairns

Zhongqi Liu

Qinrong Zhu

Hong Ji

Jerry Qian

Oliver Ou

James Osborn

Sarah Gloeckner

John Beiler

Glenn Alan Cavanaugh

Sean Philip Kearney

Allan Wirth

Peter Bressler

Andrew J Jankevics

Gregory Mark Rueblinger

Russell Joseph Dobbs

Charles Joseph Cunningham, Iv

Mark Meagher

William Svedas

Douglas M Hinson

Jeffery Yorsz

Robert H Brady

Daniel James Olson

Robert M Pierce

Manjul Bizoara

Malcolm Gillespie

Steve Y Kim

Sri Teja Gadamsetti

Harry C Knowles

Wei Zhao

Jingzhe Zhang

Matthew Jefferson

Embodiments described include apparatuses, computer program products, and methods for automatic proof of delivery, for example by capturing and decoding a visual indicia. Some embodiments minimize possibilities of errors, false proof, and/or the like in item delivery. At least one embodiment enables automatic proof of delivery in a multi-sensor environment. Example embodiments are configured for capturing an image data object set utilizing at least one of an image sensor set, where the image data object set includes a captured-indicia image data object including a visual indicia; decoding the visual indicia to identify delivery information; identifying a delivery proof image data object from the image data object set; and processing the delivery proof image data object for use as a proof of delivery. Some embodiments include a near-field image sensor for capturing the delivery proof image data object and a far-field sensor for capturing the captured-indicia image data object.

Apparatuses, methods, and computer program products for automatic proof of delivery using visual indicia

The various embodiments illustrated herein disclose a method for operating an imaging device. the method includes activating a first image sensor at a first duty cycle within a first time period. The method further includes activating a second image sensor at a second duty cycle within the first time period. Additionally, the method includes modifying at least one of the first duty cycle or the second duty cycle based on at least a workflow associated an operator of the imaging device.

Systems and methods for operating an imaging device

Various embodiments described herein provide implementations for controlling flicker, for example caused by a plurality of light sources, in a multi-sensor environment. Various embodiments provided utilize a broadest illuminator source for capturing image data objects for processing. The broadest illuminator source minimizes the number of activation changes required between the various illuminator sources. One example embodiment includes activating a broadest illuminator source of a plurality of illuminator sources; determining, based on a plurality of image sensors and an sensor activation sequence, a chosen image sensor of the plurality of image sensors for an image processing operation; and activating a chosen illuminator source of the plurality of illuminator sources, the chosen illuminator source associated with the chosen image sensor.

Apparatuses and methodologies for flicker control

Embodiments of the disclosure relate generally to flicker reduction in a multi-imager environment. Embodiments include methods, computer program products, and apparatuses for producing a near-field illumination using a near-field illuminator, the near-field illumination produced at a defined pulse train. A near-field image sensor may be exposed near the start of a near-field illumination pulse, and a far-field image sensor may be exposed between pulses of the near-field illumination. Some embodiments, additionally or alternatively, are configured for detecting an illuminator switch event, deactivating the near-field illuminator source, and producing, using a far-field illuminator source, a far-field illumination. Upon switching the illuminator source, some such embodiments are configured for exposing a far-field illuminator near the start of the far-field illumination pulse, and exposing a near-field image sensor near the start of the next available far-field illumination pulse. Such image capture may repeat until a task such as barcode reading is successful.

Apparatuses, methods, and computer program products for flicker reduction in a multi-sensor environment

Embodiments of the disclosure relate generally to flicker reduction in a multi-imager environment. Embodiments include methods, computer program products, and apparatuses configured for producing a near-field illumination using a near-field illuminator, the near-field illumination produced at a defined pulse train. A near-field image sensor may be exposed near the start of a near-field illumination pulse, and a far-field image sensor may be exposed between pulses of the near-field illumination. Some embodiments, additionally or alternatively, are configured for detecting an illuminator switch event, deactivating the near-field illuminator source, and producing, using a far-field illuminator source, a far-field illumination. Upon switching the illuminator source, some such embodiments are configured for exposing a far-field illuminator near the start of the far-field illumination pulse, and exposing a near-field image sensor near the start of the next available far-field illumination pulse. Such image capture may repeat until an image processing task such as barcode reading is successful.

A scanning apparatus and associated charging system are provided that include a universal power interface configured to receive a removable power source connected thereto where the removable power source includes a power storage unit and a charging circuit. The scanning apparatus further includes scanning circuitry that is in electrical communication with the universal power interface and is configured to scan a target. The scanning apparatus further includes a processor communicably coupled with the scanning circuitry and the universal power interface. In an instance in which the universal power interface receives the removable power source, the processor is configured to determine a type of the removable power source, select one or more parameters based on the determined type of the removable power source, and operate at least one of the scanning apparatus or the charging circuit in the removable power source based on the one or more selected parameters.

Scanning apparatus and modular power source

Embodiments of the present disclosure include apparatuses, computer-implemented methods, and computer program products for automatic product verification and shelf product gap analysis. Some embodiments utilize a multi-imager imaging engine to capture at least two image data objects associated with at least a near field and a far field via corresponding near and far-field imagers. The far field image data object in some embodiments is processed to identify, and/or detect and decode, product information on a product label at a shelving location for future processing. The near-field image data object may be processed to identify a product set located within the environment surrounding the product label. The information identified from each image data object may be processed to identify whether one or more product mismatches, pricing mismatches, and/or product gaps are present at the shelving location, with improved likelihood of success for each task.

Apparatuses, computer-implemented methods, and computer program products for automatic product verification and shelf product gap analysis

Apparatuses, computer-implemented methods, and computer program products for flicker reduction in a multi-sensor environment

Growing community of inventors

Sewell, NJ, United States of America

David M Wilz