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Image-Based Stamp Extraction for Enhanced Postal Automation

Authors: Haidong Yuan; Huadong Ma; Xiaodong Huang;

Image-Based Stamp Extraction for Enhanced Postal Automation

Abstract

Postal automation is yet a partially solved challenge, and part of the challenge is the automatic and accurate extraction of stamps in envelope. We observed that the stamp perforations form a distinct boundary between the stamps and the background. The number and the linear distribution of stamp perforations can be utilized to extract and validate each stamp accurately. In this paper we approach this problem by proposing a novel stamp extraction and validation algorithm. First, the character of stamp boundary is emphasized and extracted through the RGB Components Absolute Difference under Variant Illumination Condition (CADVIC). Second, the stamp perforations are validated based on correlation matching, and then Hough Transform is exploited to generate the borderlines of each stamp. A number of experiments show our method is effective.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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