Digital imaging technology continues to improve and find widespread acceptance in both consumer and industrial applications. Digital imaging readers are now commonplace in video movie cameras, security cameras, video teleconference cameras, machine vision cameras and, more recently, hand-held symbology readers. As each application matures, the need for intelligent image processing techniques grows. To date, the large data volume attendant to transmitting a digital image from one location to another could only be accomplished if the two locations were connected by a wired means. Machine vision and other image processing applications required significant computing power to be effective and correspondingly require too much power to be useful in portable applications. The trend now in both consumer and industrial markets is toward the use of portable wireless imaging that incorporates automatic identification technology.
Historically, the automatic identification industry has relied on laser technology as the means for reading symbology. Laser scanners generate a coherent light beam that is oriented by the operator to traverse the horizontal length of the symbology. The reflected intensity of the laser beam is used to extract the width information from the bars and spaces that are encountered. Laser scanners are effective in reading linear symbology such as the U.P.C. code found in retail point-of-sale applications, Code 39, Interleaved 2 of 5, or the like. Information stored in these linear (1D) symbologies is used to represent a short message or an index number related to a separate data file located in a central computer.
Imaging-based scanners use a solid-state image sensor such as a Charge Coupled Device (CCD) or a Complimentary Metal Oxide Semiconductor (CMOS) imager to convert an image scene into a collection of electronic signals. The image signals are processed so that any machine-readable character or symbology found in the field of view can be located in the electronic representation of the image and subsequently interpreted. The ability of image-based readers to capture an electronic image of a two-dimensional area for later processing makes them well suited for decoding all forms of machine-readable symbology at any orientation.
An image-based scanner is made up of an optical imaging chip, light-emitting diodes (LEDs), a lens or lenses, a targeting means and other optical components such as wedges or diffusers. The lens is often attached to the module housing by a threaded assembly which, when tightened and locked, holds the lens at a specific fixed focal distance from the imaging array plane. An illumination board contains the LEDs and targeting means for aiming the target symbology. The lens projects through an aperture in the illumination board which is also held in place by the module housing.
Generally, as in laser scanners, there are different types of cameras to image different types or sizes of symbologies. They include ultra high definition (UHD), high definition (HD), standard (ST) and ultra long range (ULR). These cameras have a different focal distance for each of these different applications. This means that the lens is at a different distance from the imager in each of these cameras in order to provide the different focal ranges required to adequately resolve and decode the target symbology in the intended application.
The distance between the imaging array and the lens determines the focal range of the camera module. Generally, this distance is calibrated and then fixed within the module assembly. To have an auto-focusing system, similar to those found in regular cameras would greatly impact the size, cost and power consumption, making it an impractical feature for camera modules of the type found in image readers. Therefore, it is necessary to configure a separate camera module to accommodate the focal range of different symbology feature sizes.
There are a number of prior art technique which try to overcome the problem of imaging at different focal lengths. A traditional technique includes the implementation of 2 free space optical elements, whereby each element has a different fixed focal lengths. Another technique includes the use of a single objective lens that is moved between different fixed focal points such as those used in automatic focus cameras. While these techniques do offer some advantages over typical single free space objective lens systems, they still provide limited optical depth of field.
U.S. Pat. No. 5,765,981, which issued to Roustaei et al on May 26, 1998, describes a technique used in a camera module having a lens assembly, which contains multiple lenses. The lenses are moved apart in relation to each other by a solenoid or motor. This allows the camera to image the symbology at different focal ranges. This technique however, still provides a limited optical depth of field. Further, the use of a motor or solenoid makes this option expensive and impractical for applications requiring inexpensive components. It is also expected that this would result in a significant latency in the decoding operation as the image is analyzed and the lenses are moved to the desired position. This latency would result in a loss of reading performance to the end user. Additionally, the use of the mechanism to driver the lens assembly can also be prone to performance issues related to the sensitivity of this type of mechanism to mechanical shock or vibration.
U.S. Pat. No. 6,340,114, which issued to Correa et al on Jan. 22, 2002, describes a technique in which the lens assembly comprises two lenses each having a different focal range. A moving optical element such as a mirror is provided to select an image through either the first or second lens. This technique still provides limited depths of field. This technique is also quite complex and requires numerous extra features including dedicated mirrors, and mechanical means such as an electronic servomechanism to control the mirrors. These extra features would make this technique expensive and impractical for a variety of imaging applications such as image readers and barcode readers. The addition of mirrors with servomechanisms also introduces the potential for a loss of mechanical robustness. This type of mechanism is typically used in laser scanners and often the cause of either a loss of performance or functionality due to damage from mechanical shock or vibration.
U.S. Pat. No. 5,748,371, which issued to Cathey Jr. et al on May 5, 1998, describes an apparatus that uses optical encoding and image processing to provide an extended optical depth of field. This is known as a Wavefront Coded™ lens system. The light traveling through a Wavefront Coded™ lens system does not focus on a specific focal plane due to a special surface or mask that is placed in the lens system. No points of the object are imaged as points on the focal plane. Instead, the points are uniformly blurred over an extended range about the focal plane. This special surface can be thought as “encoding” the light passing through the lens system. None of the light passing through this system converges at the focal plane as it would in a traditional free-space objective lens system. Since the image is blurred, signal processing is required to “decode” the blurred image. In traditional optical lens systems, clear images are achieved at the expense of depth of field. In the Wavefront Coded™ lens system, the pre-processed image will contain misfocus aberrations, but will have an extended depth of field. Signal processing and filtering within the Wavefront Coded™ lens system cleans the image while still maintaining the extended depth of field. The primary intended application for this apparatus, however, does not include detecting and decoding symbologies.
U.S. Pat. No. 6,152,371, which issued to Schwartz et al on Nov. 28, 2000, and U.S. Pat. No. 6,547,139, which issued to Havens et al on Apr. 15, 2003, describe a barcode scanner, which uses a cubic phase mask similar to the process described in U.S. Pat. No. 5,748,371 noted above. While this invention modifies the Wavefront Coded™ lens system for the application of detecting and decoding barcode symbols, it does so at the expense of time. Traditional optical elements can image barcode symbologies on average in 100 milliseconds or less. Wavefront Coded™ based lens systems do so at rates of 10 seconds. As well, the current state of barcode decoding algorithms do not require a high level of optical resolution to effectively detect and decode a barcode in an image scene. The improvement this invention provides in optical depth of field does not necessarily result in an increased barcode depth of reading. This approach would increase cost and decode speed, while yielding questionable benefit from a barcode decoding depth of reading.
Therefore there is a need for an imaging system to detect and decode symbologies and other targets in a time efficient manner while at the same time providing an extended depth of field.