Abstract: An image, represented by an ordered set of elements (xi) each having a value is analysed in order to detect vanishing points. The method comprises, for each of a plurality of root positions (x0), repeatedly performing the steps of: (i) selecting a first plurality of elements (xi) from the ordered set; (ii) for each selected element (xi), selecting a second element (ui) such that the selected second element has a vector position relative to the root position that is scaled by a factor (?) in comparison with the position of the first selected element; (iii) determining whether the selected elements meet a match criterion requiring that the value of each of the first elements is similar to the value of the corresponding second element; and (iv) in the event of a match, updating a similarity score (H) in respect of that root element. Once these scores have been found, they can be examined a part of the image corresponding to a peak value of the similarity score.

Abstract: The demodulation process of a wireless data transmission system using multi-level symbols makes use of templates corresponding to each of the possible symbol transitions, so that knowledge of previously decoded symbols can be used to decode the next one. An estimation and correction loop provides for initial estimation of the values of a plurality of consecutive symbols, and error estimates are made for the estimated initial values of the symbols and for one or more alternative values, a final estimate being determined to minimize the total estimated error.

Abstract: A camera or other optical system is focused by generating a plurality of digital images each obtained with a different focus setting of the optical system. These images are analysed to generate for each image a score (S) by comparing first groups of pixels chosen from the image with second groups chosen from the image such that the pixels of each second group have same respective positional relationships with respect to one another as the pixels of the first group with which it is compared have to one another, the score (S) being a function of the number of matches obtained with said comparisons. The focus setting that gives the score corresponding to the largest number of matches is chosen.

Abstract: Picture elements of a digitally coded image are each represented by a color value. The value of an element x is adjusted by firstly making a number of comparisons between elements elsewhere in the image. This comparison involves comparing a first picture element group (which may comprise the picture element x under consideration and at least one further picture element in the vicinity thereof) with a second picture element group. The second picture element group comprises a base picture element y and at least one further picture element, the number of picture elements in the second group being the same as the number of picture elements in the first group and the position of each further element of the second group relative to the base picture element of the second group being the same as the position of the respective further element of the first group relative to the picture element under consideration.

Abstract: A camera or other optical system is focused by generating a plurality of digital images each obtained with a different focus setting of the optical system. These images are analysed to generate for each image a score (S) by comparing first groups of pixels chosen from the image with second groups chosen from the image such that the pixels of each second group have same respective positional relationships with respect to one another as the pixels of the first group with which it is compared have to one another, the score (S) being a function of the number of matches obtained with said comparisons. The focus setting that gives the score corresponding to the largest number of matches is chosen.

Abstract: A first pattern (A) is represented by a first ordered set of elements (xi) each having a value whilst a second pattern (B) is represented by a second ordered set of element (ui) each having a value. The patterns are analysed by iteratively performing the steps of: selecting (e.g.

Abstract: An image, represented by an ordered set of elements (xi) each having a value is analysed in order to detect vanishing points. The method comprises, for each of a plurality of root positions (x0), repeatedly performing the steps of: (i) selecting a first plurality of elements (xi) from the ordered set; (ii) for each selected element (xi), selecting a second element (ui) such that the selected second element has a vector position relative to the root position that is scaled by a factor (?) in comparison with the position of the first selected element; (iii) determining whether the selected elements meet a match criterion requiring that the value of each of the first elements is similar to the value of the corresponding second element; and (iv) in the event of a match, updating a similarity score (H) in respect of that root element. Once these scores have been found, they can be examined a part of the image corresponding to a peak value of the similarity score.

Abstract: A database of visual images includes metadata having, for a particular image, at least one entry specifying: a part of that image, another stored image, and a measure Sabi of the degree of similarity between that specified part and the specified other image. One or more images are displayed and input is received from a user (for examples, by using a gaze tracker) indicative of part of the displayed images. Measures of interest are determined for each of a plurality of non-displayed stored images specified by the metadata for the displayed image(s), as a function of the similarity measure(s) and the relationship between the user input and the part specified. On the basis of these measures, a selection is made from those non-displayed stored images of further images for display.

Abstract: A first visual image or other pattern (A) is represented by a first ordered set of elements (xi) each having a value and a second pattern (B) is a represented by a second ordered set of element (ui) each having a value.

Abstract: A first image (or other pattern) is represented by a first ordered set of elements A each having a value and a second pattern is represented by a second such set. A comparison of the two involves performing, for each of a plurality of elements x of the first ordered set the steps of selecting from the first ordered set a plurality of elements x? in the vicinity of the element x under consideration, selecting an element y of the second ordered set and comparing the elements x? of the first ordered set with elements y? of the second ordered set (each of which has the same position relative to the selected element y? of the second ordered set as a respective one x? of the selected plurality of elements of the first ordered set has relative to the element x under consideration).

Abstract: This invention identifies anomalies in a data stream, without prior training, by measuring the difficulty in finding similarities between neighborhoods in the ordered sequence of elements. Data elements in an area that is similar to much of the rest of the scene score low mismatches. On the other hand a region that possesses many dissimilarities with other parts of the ordered sequence will attract a high score of mismatches. The invention makes use of a trial and error process to find dissimilarities between parts of the data stream and does not require prior knowledge of the nature of the anomalies that may be present. The method avoids the use of processing dependencies between data elements and is capable of a straightforward parallel implementation for each data element. The invention is of application in searching for anomalous patterns in data streams, which include audio signals, health screening and geographical data. A method of error correction is also described.

Abstract: A first visual image or other pattern (A) is represented by a first ordered set of elements (xi) each having a value and a second pattern (B) is a represented by a second ordered set of element (ui) each having a value.

Abstract: The most significant features in visual scenes, is identified without prior training, by measuring the difficulty in finding similarities between neighbourhoods in the scene. Pixels in an area that is similar to much of the rest of the scene score low measures of visual attention. On the other hand a region that possesses many dissimilarities with other parts of the image will attract a high measure of visual attention. A trial and error process is used to find dissimilarities between parts of the image and does not require prior knowledge of the nature of the anomalies that may be present. The use of processing dependencies between pixels avoided while yet providing a straightforward parallel implementation for each pixel. Such techniques are of wide application in searching for anomalous patterns in health screening, quality control processes and in analysis of visual ergonomics for assessing the visibility of signs and advertisements.

Abstract: This invention identifies the most significant features in visual scenes, without prior training, by measuring the difficulty in finding similarities between neighbourhoods in the scene. Pixels in an area that is similar to much of the rest of the scene score low measures of visual attention. On the other hand a region that possesses many dissimilarities with other parts of the image will attract a high measure of visual attention.

Abstract: A speech synthesizer (3) produces prompts in the voice of a native speaker of a language to be learned to which the student replies or imitates. A phrase recognizer (1) employs keyword recognition to generate from the student's prompted response an original speech template spoken by the student. Thereafter, interactive dialogue takes place. The student's progress in that dialogue is monitored by measuring the deviation of the student's current speech from his original speech template. When this deviation is sufficiently large so that the recognizer (1) no longer recognizes what the student is saying, the system retrains and updates the student's speech template. In another embodiment, the system includes a display which shows the native speaker's mouth shape while the words to be imitated are spoken by the speech synthesizer (3). Also provided are a video pick-up and analyzer for analyzing the shapes of the student's mouth to give the student visual feedback.

Abstract: A waveform recognition system including a plurality of detectors of features having the combined presence at a plurality of instants spaced at predetermined intervals relative to each other in time of instantaneous amplitudes each satisfying respectively predetermined constraints; apparatus for assigning a plurality of labels and corresponding confidence measures to each of successive portions of the waveform in dependence on the features detected in the portions and storing each label in a buffer corresponding to the rank of the confidence with which the label is assigned relative to other labels assigned to the same portion of data and apparatus for outputting labels from that buffer containing labels assigned with the highest confidence whose confidence measures are in a predetermined relationship with those of adjacent labels in the same buffer when the confidence measures of labels in other buffers containing labels assigned with confidence measures of lower rank satisfy predetermined conditions.

Abstract: A pattern recognition system comprising pattern scanning data input means (1), a dichotomizing device (3), a feature matching device (5), a label assignment circuit (7) and a syntactic decision processing device (9). The label assignment circuit assigns labels and confidence measures to data corresponding to successive areas of the pattern. The syntactic decision processing device (9) comprises a buffer for storing area values comprising positional information, corresponding labels and confidence measures for adjacent areas in the pattern forming a two dimensional array and also comprises decision means for outputting labels and positional information for those areas whose confidence measures form two dimensional maxima with respect to those for neighboring areas in the array. The system may operate continuously as area values corresponding to successive portions of input data are added to the buffer.