A comparative analysis of two distance measures in color image databases
نویسندگان
چکیده
Euclidean distance measure has been used in comparing feature vectors of images, while cosine angle distance measure is used in document retrieval. In this paper, we theoretically analyze these two distance measures based on feature vectors normalized by image size and experiment with them in the context of color image database. We find that the cosine angle distance, in general, works equally well for image databases. We show, for a given query vector, characteristics of feature vectors that will be favored by one measure but not by the other. We compute k-nearest neighbors for query images using both Euclidean and cosine angle distance for a small image database. The experimental data corroborate our theoretical results.
منابع مشابه
Robust Potato Color Image Segmentation using Adaptive Fuzzy Inference System
Potato image segmentation is an important part of image-based potato defect detection. This paper presents a robust potato color image segmentation through a combination of a fuzzy rule based system, an image thresholding based on Genetic Algorithm (GA) optimization and morphological operators. The proposed potato color image segmentation is robust against variation of background, distance and ...
متن کاملComparative study of histogram distance measures for re-identification
Color based re-identification methods usually rely on a distance function to measure the similarity between individuals. In this paper we study the behavior of several histogram distance measures in different color spaces. We wonder whether there is a particular histogram distance measure better than others, likewise also, if there is a color space that present better discrimination features. S...
متن کاملAn Empirical Study and Comparative Analysis of Content Based Image Retrieval (CBIR) Techniques with Various Similarity Measures
Content Based Image Retrieval (CBIR) is a process in which for a given query image similar images will be retrieved based on the image content similarity. Image content refers to its visual features, which are mathematical representations of a digital image. The image retrieval task primarily depends on image feature extraction and similarity measurement between the feature vectors. The perform...
متن کاملComparative Study on CBIR based on Color Feature
Content Based Image Retrieval (CBIR) system helps users to retrieve relevant images based on their contents. It finds images in large databases by using a unique image feature such as texture, color, intensity or shape of the object inside an image. This paper presents a comparative study between the feature extraction techniques that based on color feature. These techniques include Color Histo...
متن کاملEfficient Image Retrieval with Statistical Color Descriptors
Color has been widely used in content-based image retrieval (CBIR) applications. In such applications the color properties of an image are usually characterized by the probability distribution of the colors in the image. A distance measure is then used to measure the (dis-)similarity between images based on the descriptions of their color distributions in order to quickly find relevant images. ...
متن کامل