Bird Nest Images Classification Based on Canny Edge Detection and Local Binary Pattern
نویسنده
چکیده
This paper presents a way to classify between the nest image and the non-nest image. The input image is processed by Canny Edge Detection, and using Local Binary Pattern to extract the local textural features. K-means was applied to clustering LBP feature. And, dividing images into several blocks and finding out the dominant local textural features for describing the corresponding block. The performance of this method is tested by support vector machines, random forest and K-nearest neighbors.
منابع مشابه
Second-Order Statistical Texture Representation of Asphalt Pavement Distress Images Based on Local Binary Pattern in Spatial and Wavelet Domain
Assessment of pavement distresses is one of the important parts of pavement management systems to adopt the most effective road maintenance strategy. In the last decade, extensive studies have been done to develop automated systems for pavement distress processing based on machine vision techniques. One of the most important structural components of computer vision is the feature extraction met...
متن کاملEdge Detection Based On Nearest Neighbor Linear Cellular Automata Rules and Fuzzy Rule Based System
Edge Detection is an important task for sharpening the boundary of images to detect the region of interest. This paper applies a linear cellular automata rules and a Mamdani Fuzzy inference model for edge detection in both monochromatic and the RGB images. In the uniform cellular automata a transition matrix has been developed for edge detection. The Results have been compared to the ...
متن کاملMandibular Trabecular Bone Analysis Using Local Binary Pattern for Osteoporosis Diagnosis
Background: Osteoporosis is a systemic skeletal disease characterized by low bone mineral density (BMD) and micro-architectural deterioration of bone tissue, leading to bone fragility and increased fracture risk. Since Panoramic image is a feasible and relatively routine imaging technique in dentistry; it could provide an opportunistic chance for screening osteoporosis. In this regard, numerous...
متن کاملEdge Detection Based On Nearest Neighbor Linear Cellular Automata Rules and Fuzzy Rule Based System
Edge Detection is an important task for sharpening the boundary of images to detect the region of interest. This paper applies a linear cellular automata rules and a Mamdani Fuzzy inference model for edge detection in both monochromatic and the RGB images. In the uniform cellular automata a transition matrix has been developed for edge detection. The Results have been compared to the ...
متن کاملNoisy images edge detection: Ant colony optimization algorithm
The edges of an image define the image boundary. When the image is noisy, it does not become easy to identify the edges. Therefore, a method requests to be developed that can identify edges clearly in a noisy image. Many methods have been proposed earlier using filters, transforms and wavelets with Ant colony optimization (ACO) that detect edges. We here used ACO for edge detection of noisy ima...
متن کامل