Content-Based Image Retrieval Using Texture Color Shape and Region

Shirazi, Syed Hamad; Umar, Arif Iqbal; Naz, Saeeda; Khan, Noor ul Amin; Razzak, Muhammad Imran; Alhaqbani, Bandar

doi:10.14569/ijacsa.2016.070156

Cited by 10 publications

(2 citation statements)

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“…Millions of digital imaging machines have revolutionized conventional photography over the past decade and into the late twentieth century, producing billions of digital images. Due to the huge volume of digital images on Internet and their diversity, large and small digital libraries have been produced around the world, which has led to manage image databases and use tools for image retrieval and classification [1].…”

Section: Introductionmentioning

confidence: 99%

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A hybrid approach for categorizing images based on complex networks and neural networks

Ebrahimi

Mirzaie

Latif

2022

IJECE

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There are several methods for categorizing images, the most of which are statistical, geometric, model-based and structural methods. In this paper, a new method for describing images based on complex network models is presented. Each image contains a number of key points that can be identified through standard edge detection algorithms. To understand each image better, we can use these points to create a graph of the image. In order to facilitate the use of graphs, generated graphs are created in the form of a complex network of small-worlds. Complex grid features such as topological and dynamic features can be used to display image-related features. After generating this information, it normalizes them and uses them as suitable features for categorizing images. For this purpose, the generated information is given to the neural network. Based on these features and the use of neural networks, comparisons between new images are performed. The results of the article show that this method has a good performance in identifying similarities and finally categorizing them.

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Section: Introductionmentioning

confidence: 99%

“…For example, Ramesh introduced a histogram-based system that uses histogram characteristics to categorize images [3]. Moreover, Shirazi et al [1] compared the various methods used by the vector machine for categorizing the images. Shakoor et al [2] used a local entropy method to identify the image features and used them for categorization.…”

Section: Introductionmentioning

confidence: 99%