Abstract:
A method and apparatus for decoding a two-dimensional bar code symbol using a charge-coupled device (CCD) camera, charge-modulation device (CMD) camera, or other bar code reading device such as a hand-held reader, light pen or wand, scan mouse, or stationary laser scanner. The CCD/CMD camera or reading device optically images the bar code symbol to obtain digital image data, which is stored in a memory. The location and orientation of the two-dimensional bar code
Abstract:
A method and apparatus for decoding a two-dimensional bar code symbol using a charge-coupled device (CCD) camera or a charge-modulation device (CMD) camera. The CCD/CMD camera takes pictures of the symbol and the picture is converted into digital data. The location and orientation of the two-dimensional bar code symbol is determined and verified. Defects and damages on the symbol are detected and corrected. The symbol is scanned to read the codewords of the two-dimensional bar code symbol.
Abstract:
A statistical basis for use in a self-scanning checkout system determines how many items to check in a shopper's shopping cart for incorrect or missing scans as well as which particular or types of items to check to determine if they were properly scanned, if the shopper is determined to be audited. The present invention does not audit every customer, but rather determines whether a given shopper or customer is to be audited on a given shopping trip based upon obtaining a minimum checkout loss for such customer. The methodology determines how many items to check for a given shopper as well as which particular items to check for that shopper. The following factors attempt to model the real world of shopping and may be considered, alone or in varying combinations, in determining the number of items to check for a particular shopping transaction: shopper frequency; queue length; prior audit history; store location; time of day, day of week, date of year; number of times items are returned to shelf during shopping; dwell time between scans; customer loyalty; store shopping activity and other factors. Using statistical decision theory for auditing policies a minimum loss per shopper transaction improves the security and reduces the labor of self-check out without being too intrusive to customers.
Abstract:
A portable data input or computer system includes an input/output device such as a keyboard and a display, another data input device such as an optical bar code scanner, and a data processor module. To scan bar code type indicia, the operator points the scanner at the bar code and triggers the scanner to read the indicia. All the system components are distributed on an operator's body and together form a personal area system (PAS). Components may include a scanner or imager, a wrist unit, a headpiece including an eyepiece display, speaker and a microphone. Components within a particular PAS communicate with each other over a personal area network (PAN). Individual PASs may be combined into a network of PASs called a PAS cluster. PASs in a particular PAS cluster can communicate with each other over another wireless communication channel. Individual PAS can gain access to a Local Area Network (LAN) and/or a Wide Area Network (WAN) via an access point. Individual PASs can use devices, such as servers and PCs situated either on the LAN or the WAN to retrieve and exchange information. Individual PAS components can provide automatic speech and image recognition. PAS components may also act a telephone, a pager, or any other communication device having access to a LAN or a WAN. Transmission of digitized voice and/or video data can be achieved over an Internet link.
Abstract:
A statistical basis for use in a self-scanning checkout system determines how many items to check in a shopper's shopping cart for incorrect or missing scans as well as which particular or types of items to check to determine if they were properly scanned, if the shopper is determined to be audited. The present invention does not audit every customer, but rather determines whether a given shopper or customer is to be audited on a given shopping trip based upon obtaining a minimum checkout loss for such customer. The methodology determines how many items to check for a given shopper as well as which particular items to check for that shopper. The following factors attempt to model the real world of shopping and may be considered, alone or in varying combinations, in determining the number of items to check for a particular shopping transaction: shopper frequency; queue length; prior audit history; store location; time of day, day of week, date of year; number of times items are returned to shelf during shopping; dwell time between scans; customer loyalty; store shopping activity and other factors. Using statistical decision theory for auditing policies a minimum loss per shopper transaction improves the security and reduces the labor of self-check out without being too intrusive to customers.
Abstract:
Transmitting devices facilitate privacy protection of content broadcasted from the transmitting device to a receiving device without the need to modify the receiving device. A transmitting device may be adapted to acquire content, such as audio and/or video data, to be broadcasted by the transmitter for reception and use by a receiving device. A transmission range is selected to define a distance for broadcasting the content from the transmission device for reception and use by a receiving device. A frequency is also selected to be used for broadcasting the content. With the transmission range and frequency selected, the transmitting device may broadcast the content according to the selected transmission range and frequency.
Abstract:
A method includes generating, at a low rate enabler (LRE) device, a packet including a preamble having a legacy portion and a super long range (SLR) portion. The legacy portion includes at least one bit to indicate a presence of the SLR portion to at least one SLR-compatible device. The method also includes transmitting the packet to a plurality of devices includes the at least one SLR-compatible device.
Abstract:
A decentralized approach to peer discovery channel selection is used in some embodiments. In some such embodiments, a mobile wireless terminal supporting a peer to peer signaling protocol, independently determines what channels to use for peer discovery without a central controller indicating the channel or channels to be used. Assuming channels are of a suitable quality, the channels having the best quality need not be identified, with channel selection being made on a predetermined channel ordering basis from those with suitable quality. Different wireless communications devices in the system use the same peer discovery channel selection process making it likely that the same channel or channels will tend to be picked to be used for peer discovery. Other embodiments are directed to implementing a centralized approach to peer discovery channel selection in which a central controller or base station selects channels to be used for peer discovery signaling.
Abstract:
In general, techniques are described for sensing wireless communications in television frequency bands, which may be implemented by a sensing device comprising a sensing unit, a power spectral density (PSD) estimation unit, a filter unit, a candidate selection unit, an analysis unit and a decision unit. The sensing unit senses a signal in the television frequencies bands. The PSD estimation unit calculates an estimate of a PSD for the sensed signal. The filter unit filters the estimated PSD. The candidate selection unit analyzes the filtered PSD to identify a candidate frequency representative of a potentially in use frequency. The analysis unit computes a test statistic for the candidate frequency. The decision unit compares the test statistic to a threshold to identify whether the candidate frequencies is actively in use by wireless communication devices.
Abstract:
Methods and apparatus for sensing features of a signal in a wireless communication system are disclosed. The disclosed methods and apparatus sense signal features by determining a number of spectral density estimates, where each estimate is derived based on reception of the signal by a respective antenna in a system with multiple sensing antennas. The spectral density estimates are then combined, and the signal features are sensed based on the combination of the spectral density estimates.