System and method for recovering image detail from multiple image frames in real-time

• US 8,150,163 B2
• Filed: 04/11/2007
• Issued: 04/03/2012
• Est. Priority Date: 04/12/2006
• Status: Expired due to Fees

• Current Assignee: Scanbuy Incorporated
• Original Assignee: Scanbuy Incorporated
• Inventors: Kruppa, Hannes Martin
• Primary Examiner(s): Patel, Jayesh A
• Application Number:
  US11/734,173
• Publication Number:
  US 20070242883A1
• Time in Patent Office: 1,819 Days
• Field of Search: 382/190, 382/193, 382/195, 382270-273, 382312-313, 23546001-46016
• US Class Current: 382/190
• CPC Class Codes: G06T 3/4069 by subpixel displacements
• CPC Class Codes: G06T 5/20 using local operators
• CPC Class Codes: G06T 5/73 Deblurring; Sharpening

Abstract

This invention describes an efficient super-resolution method for image enhancement that leverages prior knowledge about the specific task for which detail information is recovered. The particular case of barcode scanning is considered. The barcode localization and decoding algorithm of the present invention employs a subpixel-accurate search algorithm which allows for estimating barcode bit values at a higher resolution than that available in the image data itself. It thus allows for the synthesis of image detail from multiple frames with the result containing more detail than any of the input frames. For efficiency, it leverages special properties of the quadrilateral target object as well as prior knowledge about constant patterns in the barcodes of interest. This allows for real-time software implementations on portable devices such as camera-equipped cell phones where super-resolution helps to overcome some of the typical camera resolution and processing power constraints.

Claims

1. A method for real-time recovery of barcode features from a plurality of image frames, comprising:

(a) obtaining a first image frame from the plurality of image frames, wherein the plurality of image frames include a barcode;

(b) detecting four-corner coordinates of the barcode in the first image frame using at least one corner template;

(c) detecting a set of barcode features of the barcode based on image intensities;

(d) estimating a noise level of the detected set of barcode features using at least one barcode template;

(e) if the estimated noise level is not greater than a predetermined threshold level, collecting statistical information of the set of barcode features, wherein statistical barcode data is generated from accumulating the collected statistical information;

(f) determining whether the set of barcode features can be decoded based on the statistical barcode data;

(g) if it is determined that the set of barcode features cannot be successfully decoded based on the statistical barcode data, repeating (a)-(g) for a next image frame in the plurality of image frames; and

(h) if it is determined that the set of barcode features can be successfully decoded based on the statistical barcode data, decoding the set of barcode features to extract information encoded in the barcode, wherein the set o of barcode features could not be decoded from any one individual image frame in the plurality of image frames.

2. The method of claim 1, wherein the four-corner coordinates of the barcode are detected using a subpixel-accurate search algorithm.

3. The method of claim 1, wherein the barcode is one of one-dimensional barcode and two-dimensional barcode.

4. The method of claim 1, wherein the statistical information of the barcode features includes nonparametric histogram.

5. The method of claim 4, wherein determining whether the set of barcode features can be decoded is based on histogram peaks in the nonparametric histogram.