134 Chapter 5: Programming commands

r specifies the number of saved gray levels = scale resolution (default value = 0) as follows:

Value

Definition

 

 

0

No change from previous setting

1

Minimal noise cleaning preserving 128 gray levels

2

Low Standard noise cleaning preserving 64 gray levels

3

High Standard noise cleaning preserving 32 gray levels

 

 

4

Maximum noise cleaning preserving 16 gray levels

 

 

5

No noise cleaning and full 256 gray level as captured is preserved, default

 

 

Return: None

Description: The parameters set the image’s internal orientation and number of scanned gray levels. The internal format of the image is always 256 level gray scale, one byte per pixel; when sending to the host a reformatting (if not raw) is then done when needed. Normally 16 – 32 gray levels are suggested for viewing on displays, thus allowing more effective LZW compression while preserving distinguishable artifacts of a gray scale image. A TIFF structure is used to return all formats. This structure holds height & width and other document identifying tags as well as images of both sides.

The newest configured values are retained in non-volatile memory, persisting across power cycles.

Configure Binarization Methods and Attributes

Hexadecimal: 1D C5 nL nH m d1 – dn-1

Parameters: n is the number of bytes that follow. n values of 1 indicate a choice of threshold method only without changing methods properties. m selects the threshold method and optional attributes that the application may choose to set: m= 0 reserved for future; a dynamic function threshold method based on experience lookup tables; m = 1 (default) selects the US banking average area threshold method, m = 2 selects fixed value thresholding, m >2 reserved for future other method(s) that may be standardized by the industry. Any dx value = 0 sets the attribute at its default value. Any dx value not sent will remain unchanged.

Method

M

d1

d2

d3

 

 

 

 

 

Dynamic (Future)

0

Black bias cross point, 5

NA

NA

 

 

<=d1<=95; default =50

 

 

 

 

 

 

 

Averaging

1

% difference from average,

Reflectance below which pix is

Reflectance equal or above

 

 

5<=%<=95; default = 20%

always black; default = 51

which pix is always white;

 

 

 

 

default = 178

Fixed Threshold

2

The reflectance value to

NA

NA

 

 

be used, 1 <= d1 <= 254,

 

 

 

 

default = 96.

 

 

 

 

 

 

 

For m = 0, the bias cross point selects where favoring black pixels changes over to favoring white pixel.

The averaging method uses 20% as the default difference for a pixel to be judged different than an 1/8” square background average. Absolute values are also used to decide on a pixel’s color (either black or white).

The fixed threshold method uses a simple comparison test against the value.

Return: None

Description: This allows for selection of threshold method and tweaking of any threshold method variables. These are used when TIFF G4 binary format for the transferred image is selected.

The newest configured values are retained in non-volatile memory (persist across power cycles).

A776 (B780) Programming Guide

A776-PG00001 C 12/09

Page 146
Image 146
Cognitive Solutions B780, A776 manual Configure Binarization Methods and Attributes

B780, A776 specifications

Cognitive Solutions A776 is an advanced technology platform designed to enhance decision-making processes through the application of artificial intelligence and cognitive computing. This state-of-the-art solution seamlessly integrates multiple technologies to optimize business operations and drive innovation across various sectors, including finance, healthcare, and manufacturing.

One of the main features of A776 is its robust data processing capabilities. Leveraging powerful machine learning algorithms, the platform can analyze vast amounts of data in real-time, identifying patterns and insights that would otherwise be overlooked. This enables organizations to make informed decisions based on actionable intelligence, significantly improving efficiency and productivity.

Another key characteristic of the A776 system is its natural language processing (NLP) capability. This feature allows the platform to understand and interpret human language, making it easier for users to interact with the system and obtain valuable insights. By integrating NLP, Cognitive Solutions A776 can provide intuitive user experiences, enabling workforce members to query data using everyday language rather than complex coding skills.

The A776 is also built on a flexible architecture that supports seamless integration with existing IT ecosystems. This interoperability allows organizations to harness their current data sources while taking advantage of the innovative features offered by A776. The platform’s API support enables smooth connections with third-party tools, enhancing collaboration and expanding its range of applications.

Security is a major focus of the Cognitive Solutions A776. The platform is equipped with advanced encryption protocols and compliance measures to ensure that sensitive data is protected against breaches and unauthorized access. This commitment to security helps businesses maintain customer trust and safeguard their competitive advantage.

Scalability is another defining feature of the A776. As businesses grow and evolve, the platform can be easily adapted to meet changing demands. Whether a small startup or a large enterprise, organizations can scale their cognitive solutions according to their operational needs.

Furthermore, the Cognitive Solutions A776 is designed with user accessibility in mind. The interface features customizable dashboards that provide a clear overview of insights and performance metrics, enabling users at all levels to harness the power of cognitive computing without requiring extensive training or technical expertise.

In conclusion, Cognitive Solutions A776 is a cutting-edge platform that offers a range of features, including advanced data processing, natural language processing, robust security measures, and user-friendly design. Its flexible architecture allows it to integrate seamlessly with existing systems, making it an indispensable tool for organizations looking to leverage artificial intelligence in their decision-making processes.