Image Retrieval Using Local Majority Intensity Patterns

Abstract

AbstractThe rapidly growing use of huge image database is becoming possible with the growth of multimedia technologies. Content-based image retrieval (CBIR) is observed as an efficient method for carrying out its management and retrieval. This paper embellishes the benefit of the image retrieval system based on the information as well as key technologies. Compared to the shortcoming that only one feature of the conventional method can be used, this paper proposes a technique for image retrieval, by analyzing a vigorous component descriptor named local majority intensity patterns (LMIP) for texture image retrieval. LMIP is the referenced pixel dependent on the encompassing lion’s share pixels’ conduct included in the image. The proposed LMIP have utilized the wager dominant part of odd and even pixels individually. The exploratory results have demonstrated that the proposed LMIP descriptor has accomplished a superior acknowledgment precision than existing methods by consuming less computation time.KeywordsContent-based image retrievalColorTextureFeature extractionLocal ternary patternLocal binary pattern