Content-based image retrieval using Mix histogram
This paper presents a new method to extract image low-level features, namely mix histogram (MH), for content-based image retrieval. Since color and edge orientation features are important visual information which help the human visual system percept and discriminate different images, this method extracts and integrates color and edge orientation information in order to measure similarity between different images. Traditional color histograms merely focus on the global distribution of color in the image and therefore fail to extract other visual features. The MH is attempting to overcome this problem by extracting edge orientations as well as color feature. The unique characteristic of the MH is that it takes into consideration both color and edge orientation information in an effective manner. Experimental results show that it outperforms many existing methods which were originally developed for image retrieval purposes.
Code (0)
등록된 구현이 없습니다.
Tasks
Content-Based Image RetrievalImage RetrievalRetrievalSimilar Papers 제목 키워드 기반
Comparative Study and Optimization of Feature-Extraction Techniques for Content based Image Retrieval
The aim of a Content-Based Image Retrieval (CBIR) system, also known as Query by Image Content (QBIC), is to help users to retrieve relevant images based on their contents. CBIR technologies provide a method to find imag…
Content-Based Image RetrievalImage CroppingImage RetrievalRetrievalImage Retrieval using Histogram Factorization and Contextual Similarity Learning
Image retrieval has been a top topic in the field of both computer vision and machine learning for a long time. Content based image retrieval, which tries to retrieve images from a database visually similar to a query im…
Content-Based Image RetrievalImage RetrievalRetrievalContent-based jewellery item retrieval using the local region-based histograms
Jewellery item retrieval is regularly used to find what people want on online marketplaces using a sample query reference image. Considering recent developments, due to the simultaneous nature of various jewelry items, v…
RetrievalA new Local Radon Descriptor for Content-Based Image Search
Content-based image retrieval (CBIR) is an essential part of computer vision research, especially in medical expert systems. Having a discriminative image descriptor with the least number of parameters for tuning is desi…
Content-Based Image RetrievalImage RetrievalRetrievalLow-Level Features for Image Retrieval Based on Extraction of Directional Binary Patterns and Its Oriented Gradients Histogram
In this paper, we present a novel approach for image retrieval based on extraction of low level features using techniques such as Directional Binary Code, Haar Wavelet transform and Histogram of Oriented Gradients. The D…
Content-Based Image RetrievalImage RetrievalRetrieval