Recognizing dataforms in image areas

• US 5,867,595 A
• Filed: 11/01/1996
• Issued: 02/02/1999
• Est. Priority Date: 06/15/1994
• Status: Expired due to Fees

• Current Assignee: Symbol Technologies, Inc. (Zebra Technologies Corporation)
• Original Assignee: Metanetics Corporation
• Inventors: Cymbalski, Robert Stanley
• Primary Examiner(s): Couso, Jose L.
• Application Number:
  US08/742,369
• Time in Patent Office: 823 Days
• Field of Search: 358/515, 382/162, 382/164, 382/165, 382/166, 382/167, 382/181, 382/182, 382/183, 382/184, 382/185, 382/187, 235/462, 235/494
• US Class Current: 382/192
• CPC Class Codes: G06V 10/255 Detecting or recognising potential candidate objects based on visual cues, e.g. shapes
• CPC Class Codes: G06V 30/2247 Characters composed of bars, e.g. CMC-7
• CPC Class Codes: G06V 30/413 Classification of content, e.g. text, photographs or tables

Abstract

Dataforms, such as bar codes and matrix codes, are recognized by analysis of histogram type data derived for a plurality of window sections of an image area. Typically, an image area 512 pixels high by 480 pixels wide is divided into 240 window areas, each including 1024 pixels in a 32 by 32 pixel square. A histogram for a window section overlying a portion of the dataform may typically exhibit two peaks representing the two principal reflective values (black and white, for example) of the elements and spaces of a dataform. A background (quiet zone) window section histogram exhibits one principal peak representing the background value (white, for example). The background window sections and the dataform window sections are assigned to two different groups. One or both groups are then used for one or more of the following: recognizing the presence of a dataform; determining whether the dataform is darker or lighter than the background; and locating the dataform within the image area. Also, a single histogram is used to identify the type of dataform, based upon the histogram signature of the dataform.

Claims

1. A method of recognizing, in an image area, a transition between:

(i) a first pattern characterized by X colors, where X is greater than 1 and (ii) a second pattern characterized by Y colors, where Y may be 1, and X and Y are different integer values, comprising the steps of;

(a) sampling pixel values, each representative of a reflective value of an incremental part of a window section of said image area, for a plurality of window sections including at least one window section overlying a portion of said first pattern, and one window section overlying a portion of said second pattern, to determine the number of occurences of each pixel value representative of the presence of different colors within each said window section;

(b) categorizing each said window section in one of the following groups;

(i) a first group for which said derived data indicates the presence of X principal colors, (ii) a second group for which said derived data indicates the presence of Y principal colors, and (iii) a third group for other window sections; and

(c) utilizing the composite positions of window sections of at least one of said groups of window sections to determine a transition between said first pattern, represented by said first group, and said second pattern, represented by said second group.

2. A method as in claim 1, wherein Y equals 1 and said second pattern is a background area of primarily a single color.

3. A method of recognizing, in an image area, a transition between:

(i) a dataform including elements and spaces characterized by X colors, where X is greater than, and (ii) a background area characterized by Y colors, where Y may be 1, and X and Y are different integer values, comprising the steps of;

(a) determining, by use of pixel values each representative of a reflective value within a section of said image area, the number of occurences of each pixel value representing the presence of different reflective values within said section;

(b) categorizing said section in one of the following groups;

(i) a first group characterized by the presence of X principal reflective values, (ii) a second group characterized by the presence of Y principal reflective values, and (iii) a third group for other image sections;

(c) repeating step (b) for at least one additional section of said image area, based on pixel values representative of reflective values within each respective section; and

(d) utilizing positions within said image area of sections of at least one of said first and second groups to determine a transition between said dataform and said background area.

4. A method as in claim 3, wherein step (a) includes deriving a form of histogram data indicative of relative levels of occurrence of pixel values representative of different colors within particular sections of said image area.

5. A method as in claim 3, wherein step (a) includes deriving a form of histogram data indicative of the number of occurences of each pixel value representative of different colors within particular sections of said image area.

6. A method of recognizing a dataform comprised of elements and spaces of at least two different colors, present in an image area including a background area of primarily a single color, comprising the steps of:

(a) determining, by use of pixel values each representative of a reflective value within a section of said image area, the number of occurences of each pixel value representing different reflective values within said section;

(b) categorizing said section in one of the following groups;

(i) a first group characterized by the presence of at least two principal reflective values and (ii) a second group characterized by the presence of one principal reflective value;

(c) repeating step (b) for at least one additional section of said image area, based on pixel values representative of reflective values within each respective section; and

(d) utilizing at least one of said first and second groups of sections for identifying at least one characteristic of the image area.

7. A method according to claim 6, wherein the step of identifying at least one characteristic of the image area includes at least one of the following steps:

(1) determining a transition between sections of said first group and sections of said second group;

(2) recognizing the presence of said dataform;

(3) recognizing the type of dataform present; and

(4) determining the location of said dataform.