Abstract: A client device and method to normalize a digital image into a universal digital color system includes a camera and a processor. The camera acquires a digital image of a color swatch and the processor converts the digital image into a RGB color image of the color swatch. The RGB color image is segmented into segments and each segment is analyzed to determine a dominant color for each segment. At least one dominant color for the color swatch is determined based on prevalence of at least one dominant color in each segment. A hexadecimal code of the universal color system is assigned to the color swatch that is closest to a digital hexadecimal value of the RGB image based on color component intensity values of the dominant color of the color swatch, thereby normalizing RGB colors of the color swatch.

Abstract: A system for normalizing, codifying and categorizing divergent color systems into a universal color system. A server connected to a communications network receives, processes, codifies and categorizes divergent color data from a merchant system. A middleware engine of the server receives a data feed comprising a plurality of color swatches or images from the merchant system, and normalizes the data feed into a common format. A server processor extracts image data comprising a plurality of product images from the normalized data feed, identifies and converts at least one dominant product color in each product image to a digital value, and assigns a hexadecimal code of the universal color system to each product image that is closest to the digital value of each product image based on color component intensity values of at least one dominant product color in each product image. A product categorization engine categorizes each product image into one of a plurality of product categories.

Abstract: A system for normalizing, codifying and categorizing divergent color systems into a universal color language. A server connected to a communications network receives, processes, codifies and categorizes divergent color data from a merchant system. A middleware engine of the server receives a data feed comprising a plurality of color swatches or images from the merchant system, and normalizes the data feed into a common format. A server processor extracts image data comprising a plurality of product images from the normalized data feed, identifies and converts at least one dominant product color in each product image to a digital value based on color component intensity values, and assigns a hexadecimal code of the universal color language to each product image that is closest to the digital value of each product image. A product categorization engine categorizes each product image into one of a plurality of product categories.

Abstract: A system and computer based method for transcribing and extracting metadata from a source media. A processor-based server extracts audio and video stream from the source media. A speech recognition engine processes the audio and/or video stream to transcribe the audio and/or video stream into a time-aligned textual transcription and to extract audio amplitude by time interval, thereby providing a time-aligned machine transcribed media. The server processor measures the aural amplitude of the extracted audio amplitude and assigns a numerical value that is normalized to a single, normalized, universal amplitude scale. A database stores the time-aligned machine transcribed media, time-aligned video frames and the assigned value from the normalized amplitude scale.

Abstract: A system and method for normalizing and codifying divergent color systems into a single universal color system. The middleware engine receives a data feed comprising a plurality of color swatches or images from one or more merchant system and normalizes the data feed into a common format. The dominant processor extracts the product images from the normalized data, segments each product image into segments, determines a dominant color for each segment, and determines the dominant product color for each product image based on prevalence of the dominant product color in each segment. The matched color processor converts the determined dominant product color into a digital value of the universal color system based on the color component intensity values.

Abstract: A system and computer based method for transcribing and extracting metadata from a source media. A processor-based server extracts audio and video stream from the source media. A speech recognition engine processes the audio and/or video stream to transcribe the audio and/or video stream into a time-aligned textual transcription and to extract audio amplitude by time interval, thereby providing a time-aligned machine transcribed media. The server processor measures the aural amplitude of the extracted audio amplitude and assigns a numerical value that is normalized to a single, normalized, universal amplitude scale. A database stores the time-aligned machine transcribed media, time-aligned video frames and the assigned value from the normalized amplitude scale.

Abstract: A system for normalizing, codifying and categorizing divergent color systems into a universal color language. A server connected to a communications network receives, processes, codifies and categorizes divergent color data from a merchant system. A middleware engine of the server receives a data feed comprising a plurality of color swatches or images from the merchant system, and normalizes the data feed into a common format. A server processor extracts image data comprising a plurality of product images from the normalized data feed, identifies and converts at least one dominant product color in each product image to a digital value based on color component intensity values, and assigns a hexadecimal code of the universal color language to each product image that is closest to the digital value of each product image. A product categorization engine categorizes each product image into one of a plurality of product categories.

Abstract: A system and computer based method for transcribing and extracting metadata from a source media. A processor-based server extracts audio and video stream from the source media. A speech recognition engine processes the audio and/or video stream to transcribe the audio and/or video stream into a time-aligned textual transcription and to extract audio amplitude by time interval, thereby providing a time-aligned machine transcribed media. The server processor measures the aural amplitude of the extracted audio amplitude and assigns a numerical value that is normalized to a single, normalized, universal amplitude scale. A database stores the time-aligned machine transcribed media, time-aligned video frames and the assigned value from the normalized amplitude scale.

Abstract: A system and method for normalizing and codifying divergent color systems into a single universal color system. The middleware engine receives a data feed comprising a plurality of color swatches or images from one or more merchant system and normalizes the data feed into a common format. The dominant processor extracts the product images from the normalized data, segments each product image into segments, determines a dominant color for each segment, and determines the dominant product color for each product image based on prevalence of the dominant product color in each segment. The matched color processor converts the determined dominant product color into a digital value of the universal color system based on the color component intensity values.

Abstract: A system and computer based method for transcribing and extracting metadata from a source media. A processor-based server extracts audio and video stream from the source media. A speech recognition engine processes the audio stream to transcribe the audio stream into a time-aligned textual transcription, thereby providing a time-aligned machine transcribed media. The video frame engine process the video stream to extract time-aligned video frames. A database stores the time-aligned machine transcribed media and time-aligned video frames. A server processor processes the time-aligned machine transcribed media to extract time-aligned textual metadata associated with the source media, and processes the time-aligned vide frames to extract time-aligned visual metadata associated with the source media.

Abstract: A system and method for normalizing and codifying divergent color systems into a single universal color system. The middleware engine receives a data feed comprising a plurality of color swatches or images from one or more merchant system and normalizes the data feed into a common format. The dominant processor extracts the product images from the normalized data, segments each product image into segments, determines a dominant color for each segment, and determines the dominant product color for each product image based on prevalence of the dominant product color in each segment. The matched color processor converts the determined dominant product color into a digital value of the universal color system based on the color component intensity values.

Abstract: A system and method for normalizing and codifying divergent color systems into a single universal color system. The middleware engine receives a data feed comprising a plurality of color swatches or images from one or more merchant system and normalizes the data feed into a common format. The dominant processor extracts the product images from the normalized data, segments each product image into segments, determines a dominant color for each segment, and determines the dominant product color for each product image based on prevalence of the dominant product color in each segment. The matched color processor converts the determined dominant product color into a digital value of the universal color system based on the color component intensity values.