ObjectScan 1600

Herbarium, Plants, Insects Specimen Scanning

  • 1,600-dpi color CCD provides high-resolution image
  • Adjustable scan beds are convenient for objects beyond focus
  • Up to +/- 6.5 mm DOF can get clear extended DOF images
  • Automated metadata recognition ability

Overhead On-top scan design protects fragile plant specimen

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To significantly solve digitization inefficiency common to the global herbaria museums, Microtek launches a workstation consisting of ObjectScan 1600 scanner, ScanWizard_Botany software (optional), and MiVapp_Botany archive management system (optional). This integrated workstation is characterized by, (1) On-top scan design for full-frame focus, (2) 1600 dpi (equal to 1 Gigabyte pixels) color CCD, (3) Optical Character Recognition (OCR) for specimen label and 1D barcode, and (4) image archive and privileged-account cloud management system. Both software and management system provide intuitive interface for non-IT herbarium curators and botanists, especially for herbarium inexperienced volunteers. The database structure follows JSTOR principle in order for the file exchange convenience between herbaria. Further, MiVapp_Botany can unit global academic efforts to speed up verification rate on image quality and metadata by offering remote log-in entry service. Under ideal set-up, this workstation can digitize 500,000 – 800,000 specimen per year where cost will be less than 5 USD for each specimen.

Microtek Bio-5000 Plus

On-top scan design protects fragile plant specimen.
ObjectScan 1600 is characterized as an on-top scan model. This unique mechanistic design guarantees the specimen morphological integration during image capture, eliminating irreversible risks from conventional up-side-down scan or vertically moving scanning station.

1,600-dpi color CCD provides high-resolution image.

ObjectScan 1600 has a color linear CCD with resolution up to 1,600 pixels per inch, equaling that of 1Gigabyte. With the built-in 48-bit ADC (Analog to Digital Converter), the whole specimen as well as details of surface textures can be precisely captured and presented in high fidelity format.

Up to +/- 6.5 mm DOF can get clear extended DOF images.

The DOF (Depth of Field) of ObjectScan 1600 is up to +/- 6.5 mm at 300 dpi, which can overcome uneven or protruded parts of plant specimen. This is of especially help on specimen with corns and fruits, preserving and presenting the original characters for academic purpose.

Automated metadata recognition ability.

Specimen label information will be recognized and automatically saved titled by herbarium code and specimen serial number in XML format through ScanWizard-Botany. Various options, such as contrast, lightness, and sharpness, are also provided for curators on image adjustment.


Image archive and privileged account management system

MiVapp-Botany is both a web-server system and specimen image authentication database, aiming for being an efficient and integrated multi-functional platform. After hierarchical login-based image quality and metadata profile validation from invited professionals, MiVapp-Botany can quickly update the system and immediately make verified specimen access by the public.

Additional information

Product Name

ObjectScan 1600

Scanner Type

On-top Scan Flatbed Scanner

Image Sensor Type

Color Linear CCD


1600 dpi

Light Source


Scanning Area

304.8 mm x 424.18 mm (12" × 16.7")

Scanning Speed

12 sec @ 400 dpi, A3 Color (without calibration)

Bit Depth

48-bit (Input) / 24-bit (Output)


Hi-Speed USB 2.0

Supported File Types


OS Support

Windows 7 / 8

Dimensions (L x W x H)

750 x 470 x 376 mm / 29.5" x 18.5" x 14.8" (foot stands excluded)


47 kg (103 lbs)

Power Source

AC 100V-240V, 47-63 Hz, 1.5A max. (Input) DC 15V, 2.5A (Output)

Power Consumption

37.5 W

System Requirements PC

CD-ROM drive (for installing software)
Color display with 24-bit color output capability
4 GB RAM or more
Intel Core i5 Processor at 3.0 GHz PC or higher with Hi-speed USB (USB 2.0) port
Microsoft Windows 7 / 8

Software Included

ScanWizard Graph