Advanced Recognition Technologies Inc.

Art Advanced Recognition Technologies Inc.

Optinetix (israel) Ltd.

Nuance Communications Israel Ltd.

Art Advanced Regcognition Technologies Inc.

Advanced Recognition Technology

Gabriel Ilan

Arie Kadosh

Jacob Goldberger

Meir Morag

Eran Aharonson

Benjamin Dov Giloh

Yehudah Hershkovits

Haim Perski

Doron Davidov

Shmuel Isaak

Yuval Davidor

There are disclosed systems, methods and processes for the distribution of information, typically digital information that is distributed actively, through broadcast media such as television and radio, displays, such as signage, etc., or passively, through displays such as signage or the like. The information can be captured from broadcasted transmissions, scanned from a display, or obtained by being transmitted to the user, who responded to a broadcast with a transmission to a receiving point during a period synchronized with the broadcast, requesting the information sent to his transmitted address. The captured or obtained information may include coupons or the like, that may be redeemed after being successfully captured or obtained. Redemption may be either on-line, where a transmission of coupon information is transmitted to a call center, that places a product order with a supplier and handles payment details, or off-line, where the user takes to coupon to the retailer, for redemption at the point of sale.

Systems and methods for distributing information through broadcast media

A video signal has a visual image () and carries data for optical detection () via the image. The data for optical detection is encoded () as data bits in a plurality of lines within a defined region () within the image. A corresponding decoder () uses maximal energy methods to detect the defined region prior to decoding the data.

Method and apparatus for transferring data within viewable portion of video signal

Systems and methods for embedding commercial information into broadcast media

A recognition system () for use in a vehicle or the like includes a handwriting recognizer () and a voice recognizer () for receiving handwriting and voice signals, where the signals are associated with commands used to operate with a variety of vehicle appliances. Such appliances may include, but are not limited to, car alarms (), electric windows, personal computers (), navigation systems (), and audio () and telecommunications equipment ().

Handwritten and voice control of vehicle components

A recognition system for use in a vehicle or the like includes a handwriting recognizer and a voice recognizer for receiving handwriting and voice signals and a control unit to communicate a command signal associated with one, the other or a combination of both of the voice and handwritten inputs to at least one appliance. Such appliances may include, but are not limited to, car alarms, electronic windows, personal computers, navigation systems, and audio and telecommunications equipment.

A touchpad pointing device utilized as a pattern input device for a pattern recognition system. The input pattern received from the touchpad pointing device is translated into a start application command. The recognition system forms part of a computer having an operating system and includes a touchpad pointing device, a recognition module and a signal capturer. In addition, a unit for launching an application to run on a computer having an operating system and a pointing device which produces an input pattern in response to movement upon it, is described. The unit includes a recognition module and a launcher. The recognition module attempts to recognize the input pattern as a previously trained launching pattern. The launcher launches the application by providing a launching command which is associated with the launching pattern to the operating device. A security application enables access to the computer upon receipt of an input signature from a user with access privileges.

Pattern recognition system

A vocoder based voice recognizer recognizes a spoken word using linear prediction coding (LPC) based, vocoder data without completely reconstructing the voice data. The recognizer generates at least one energy estimate per frame of the vocoder data and searches for word boundaries in the vocoder data using the associated energy estimates. If a word is found, the LPC word parameters are extracted from the vocoder data associated with the word and recognition features are calculated from the extracted LPC word parameters. Finally, the recognition features are matched with previously stored recognition features of other words, thereby to recognize the spoken word.

Speech recognition method and system using compression speech data

A handwritten pattern and stroke recognition system recognizes an input pattern by comparing it to reference patterns. The input and reference patterns comprise at least one stroke, where a stroke is defined as the series of sample points from pen-down to pen-up. The system of the present invention compares the input and reference patterns stroke by stroke and thus, compares input strokes to reference strokes. The system includes a tangent and stable point extractor, a reference database and a stable-point-based classifier. The extracter determines tangents to at least some of the sample points of the input stroke and determines, which of the sample points between a beginning and end of the input stroke are stable points. The reference database stores tangents of sample points of the reference strokes and stable points of the reference strokes. The stable-point-based classifier divides each input stroke and each reference stroke into at least two substrokes wherein each substroke has at least one of the stable points at an end thereof. The classifier also generates stroke match values indicating the quality of the match between the input stroke and the reference strokes based on the comparison of substrokes of the input stroke with corresponding substrokes of the reference strokes. The classifier selects the reference stroke providing the best match to the input stroke in accordance with a matching criterion. Finally, the classifier selects the reference pattern whose strokes best match the strokes of the input pattern.

Handwriting recognition system using substroke analysis

An instruction input unit for supplying operating instructions to a machine is provided. The unit includes a touchpad, an instruction library and a recognizer. The touchpad receives an input pattern from a user and the instruction library stores a multiplicity of operating instruction patterns. Each operating instruction pattern has an operating instruction associated therewith. The recognizer detects which of the multiplicity of operating instructions patterns the input pattern most closely matches and provides the operating instruction associated with the matched operating instruction pattern to the machine. The recognizer includes a handwriting recognizer for recognizing alphanumeric characters.

Instruction and/or identification input unit

Instruction and/or an identification input unit

A pattern recognition method of dynamic time warping of two sequences of feature sets onto each other is provided. The method includes the steps of creating a rectangular graph having the two sequences on its two axes, defining a swath of width r, where r is an odd number, centered about a diagonal line connecting the beginning point at the bottom left of the rectangle to the endpoint at the top right of the rectangle and also defining r&minus;1 lines within the swath. The lines defining the swath are parallel to the diagonal line. Each array element k of an r-sized array is associated with a separate array of the r lines within the swath and for each row of the rectangle, the dynamic time warping method recursively generates new path values for each array element k as a function of the previous value of the array element k and of at least one of the current values of the two neighboring array elements k&minus;1 and k&plus;1 of the array element k. The latter step of recursively generating new path values is repeated for all of the rows of the rectangle and the value of the middle array element is selected as the output value sought.

A handwritten pattern recognition system for recognizing an input pattern is provided. The system has a plurality of parameter determining units, each determining the value of a desired parameter for an input pattern to be recognized. The system also includes a pattern match determiner which produces match values for each parameter of the input pattern with its corresponding parameter of each reference parameter. The match determiner also produces an overall match value for each reference pattern. A pattern classifier selects the reference pattern whose parameter set is 'closest', by some matching criterion, to that of the input pattern.

Handwritten pattern recognizer with selective feature weighting

Speech recognition method and system using compressed speech data

A method for pattern recognition of indicia composed of alphabetical characters of a language in the form of at least a part of a word. The shape of each character in a word is established by means of a pattern shape recognizer. A probability value designating the relative confidence in the recognition of the character as one of the language characters is assigned to each character. The established shapes of the characters are then sequentially applied to a linguistic recognizer for further processing and the probability values of language structure to each of the language characters is assigned. Then the probability values assigned to the characters in the shape recognizer is combined with the corresponding probability values assigned to the characters in the linguistic recognizer and the path between characters possessing the highest probability values is determined.

Growing community of inventors

Tel Aviv, Israel

Gabriel Ilan