Abstract: A loudness balancing process includes three operations. In a first operation, the user specifies a plurality of digitally sampled audio time domain waveforms and an adjusted maximum loudness for each waveform is generated and stored. This operation includes a retrieve and filter process that identifies a portion of each waveform with a maximum loudness, and an adjust and store process that generates an adjusted maximum loudness that is a maximum loudness for the waveform which is free of audible distortion due to clipping. In a second operation, each stored adjusted maximum loudness is retrieved and filtered. The filtering selects a minimum adjusted maximum loudness that is selected as a global maximum loudness. In a third operation, each waveform in the plurality of waveforms is loudness-balanced based on the global maximum loudness. This three step process assures a consistent maximum loudness across the plurality of waveforms and assures that no audible noise is introduced by loudness balancing process.

Abstract: An occurrence of a predefined object in an image is recognized by receiving image data, convolving the image data with a set of predefined functions to analyze the image data into occurrences of predefined elementary features, and examining the occurrences for an occurrence of a predefined combination of the elementary features that is characteristic of the predefined object. Preferably the image data are convolved directly with a first predefined function to determine blob responses, and a second predefined function to determine ganglia responses indicating edges of objects. Then the ganglia responses are convolved with a third predefined function to determine simple responses indicating lines in the image, and the simple responses are combined with the ganglia responses to determine complex responses indicating terminated line segments in the image. A pointing finger, for example, is recognized from the combination of a blob response and a complex response.

Abstract: In order to represent a color image with a reduced quantity of information, during the transformations from color parameter pixel information to luminance/chrominance information, the first of the three luminance/chrominance parameters (i.e., the luminance) is determined for each pixel point. The two remaining luminance/chrominance parameters are determined for a predetermined pixel subarray. The luminance/chrominance subarray parameters are determined by calculating the remaining luminance/chrominance parameters for the pixel array. The remaining luminance/chrominance parameters are then determined for each pixel subarray location by calculating a weighted average of the parameters for the pixel locations that are in the neighborhood of the subarray. Only the averaged luminace/chrominance parameters for the subarray are then stored along with the first luminance/chrominance parameters for all pixels.