Polyphase decomposition is a down sampling operation that produces a set of low-resolution representations of an image. Such representations themselves are different by a phase in frequency domain, hence called polyphase components. An inter-component processing operation extracts meaningful features by performing simple logical operations over selected components. This strategy is applied to angiographic analysis to develop a fast feature-oriented vessel identification technique, which consists of polyphase decomposition on a binary image, followed by inter-component processing. The inter-component processing among selected components produces a feature map in which a non-zero pixel indicates an occurrence of a vessel geometrical feature or pattern in the original image. Using feature templates, a sequence of vessel-featured maps is generated. Fast vessel identification is performed by fusing the feature maps and displaying them according to the emergence orders of vessel geometric features, such as position, diameter, length and direction. Collective display provides a method to visualize vessel features across multiple resolutions. High-speed performance is attributed to low-resolution representation of polyphase components and simple data manipulation of inter-component processing. The tradeoff of such vessel identification technique is associated with an uncertainty for accurate measurement, arising from the inherent translations in polyphase decomposition. Therefore, accurate vessel measurements will need refinement in the original image.