Features and Benefits

  • Image Size: Configurable.
  • Input Format: 32/16 - bit PMA* output.
  • Output Format:
    • Number of detected objects
    • Properties of detected objects, such as start co-ordinates, size, margin etc.
  • Fully re-entrant and multi-instancing capable
  • Code compatible across the ADSP-BF60x and ADSP-BF70x Blackfin Processor Family
  • Framework Dependencies: None
  • Release Format: Object code module with C source wrapper.

* Polar Magnitude and Angle (PMA): is a block in PVP available in ADSP-BF609. If the bits per sample is 32, the input should be the port 2 output of the PMA block of the PVP. The lower 16 bits contain the gradient magnitude and the upper 16 bits contain the gradient angle. If the bits per sample is 16, the lower 11 bits contain the gradient magnitude and upper 5 bits contain the gradient angle information. Please refer to Hardware Reference Manual of ADSP-BF609 for more detail.

Product Details

The Blackfin HOG SVM Detector is a Software Module meant for computer vision applications targeting Blackfin family of processors. The Blackfin HOG SVM Detector comes with an optimized implementation of Histogram of Oriented Gradients (HOG) and Support Vector Machine (SVM) classifier. This Software Module can be used for detection of various objects such as people, pets, cars etc in a variety of applications.

The Blackfin HOG SVM Detector module from ADI has been highly optimized to run on the Analog Devices’ Blackfin processor family. It is a self-contained software module based on an ADI proprietary design and has been tested with a variety of images. The Blackfin HOG SVM Detector module is fully re-entrant and multi-instance capable, and comes with an intuitive API which makes it easy for system integration.

Downloads And Related Software

Software Development Tools

CrossCore® Embedded Studio

CCES is a world-class integrated development environment (IDE) for the ADI Blackfin®, SHARC® and Arm® processor families.

Software Modules

2D Graphics Primitives, Blackfin

The 2D Graphics Primitives (BF2DGL) library for the Blackfin processor implements primitives, which are based on the Open GL-ES/OpenCV APIs and are supported with wrapper example code for the OpenGL-ES/OpenCV, GLUT, and extended APIs.

Image Processing Toolbox, Blackfin

The Image Processing Toolbox library for the Blackfin processor implements a set of image processing primitives designed to enable faster development of complex image or video processing solutions.


Each module supports the Analog Devices, Inc. (ADI) Blackfin or SHARC Processor family and is a licensed product that is available in object code format. Recipients must sign or accept a license agreement with ADI prior to being shipped or downloading the modules identified in the license agreement.

Performance Metrics

MIPS summary:

  Memory (Bytes) Performance
Processor Code Stack Data RAM Data ROM Average Cycles / pel MIPS
ADSP-BF609 10708 2007 115484 6792 37.25 386
ADSP-BF707 10708
36.54 (HOG SVM Detector),
26.88 (1-D Gradient and PMA)
378 (HOG SVM Detector),
278 (1-D Gradient and PMA)

  • Performance is measured on the following processors using ADI CrossCore® Embedded Studio 2.0.0 tool-chain
    • ADSP-BF609 : CCLK = 500 MHz, SCLK = 250 MHz
    • ADSP-BF707 : CCLK = 384 MHz, SCLK = 192 MHz
  • Instruction cache and MDMA enabled. Data Cache is enabled on Bank A.
  • MIPS is calculated for a video of 720x480 resolution @ 30 fps
  • On ADSP-BF609 1-D Gradient and PMA computation is performed using PVP
  • “Data RAM” for one instance includes, scratch and state memory but excludes input/output buffers
  • Performance figures depend on configuration parameters and input vector attributes. The figures given in the table are for typical use case with following parameters.
    • Number of Classifiers: 1
    • Window Size: (64x128) with only Primary classifier
    • Window Stride: 1
  • 1 KiB = 1024 Bytes

Systems Requirements

  • Windows 7 Professional/Enterprise/Ultimate (32 and 64-bit). 
  • Minimum of 2 GHz single core processor, 3.3 GHz dual core is recommended.
  • Minimum of 1 GB memory (RAM), 4 GB is recommended.
  • Minimum of 2 GB hard disk (HDD) space is required.
  • CrossCore Embedded Studio for Analog Devices Processors.

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