Local Binary Patterns

What it is

Local Binary Patterns is an open-source library designed to extract features from images using the Local Binary Patterns technique, which is widely used in various computer vision applications such as face recognition and texture classification.

Local Binary Patterns stands out for its simplicity and efficiency in extracting local features from images, making it an ideal choice for developers and researchers focused on texture analysis and face recognition tasks.

When it fits — and when it doesn’t

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

1. 01

   Limited language support

   Primarily developed in C++, which may limit its accessibility for developers more comfortable with other languages like Python or Java.

2. 02

   Poor documentation and community support

   The official documentation lacks comprehensive examples and detailed explanations, leading to difficulties in understanding how to effectively use the library.

3. 03

   Complex setup process for non-expert users

   Setting up the environment requires a deep understanding of C++ build systems like CMake, which can be challenging for developers without extensive experience in this area.

4. 04

   Performance limitations on large datasets

   The library may exhibit slower performance when processing high-resolution images or large volumes of data, impacting real-time applications.

What it does well

• Efficient feature extraction using Local Binary Patterns

• Open-source with GPL-3.0 license

• Self-hosted and easy to integrate into existing projects

Pricing

Free tier

YesOpen source — free to use

Paid from

$0

Model

Flat rate

Enterprise plan

No

Pricing not independently confirmed — check the vendor’s page.