The improved AdaBoost algorithm application in image retrieval
نویسندگان
چکیده
Si Qing Zhang Run Zheng 1 Zhengzhou College of Science &Technology, Zhengzhou China 450064 a [email protected] Abstract—In the traditional content-based image retrieval system, for a given query image, the number of relevant images in the database are not far outnumber correlation image. Therefore, a number of negative samples and the number of positive sample is unbalanced, the two class classifier traditional lose effectiveness. In this paper, we will present the OCSVM integration method based on improved AdaBoost to solve this problem. Although OCSVM is seen as a strong classifier, in this way, we are still on the training data in AdaBoost weight updating formula was improved so that the AdaBoost can be integrated with OCSVM.
منابع مشابه
Steganography Scheme Based on Reed-Muller Code with Improving Payload and Ability to Retrieval of Destroyed Data for Digital Images
In this paper, a new steganography scheme with high embedding payload and good visual quality is presented. Before embedding process, secret information is encoded as block using Reed-Muller error correction code. After data encoding and embedding into the low-order bits of host image, modulus function is used to increase visual quality of stego image. Since the proposed method is able to embed...
متن کاملAn Improved Flower Pollination Algorithm with AdaBoost Algorithm for Feature Selection in Text Documents Classification
In recent years, production of text documents has seen an exponential growth, which is the reason why their proper classification seems necessary for better access. One of the main problems of classifying text documents is working in high-dimensional feature space. Feature Selection (FS) is one of the ways to reduce the number of text attributes. So, working with a great bulk of the feature spa...
متن کاملAn Improved Flower Pollination Algorithm with AdaBoost Algorithm for Feature Selection in Text Documents Classification
In recent years, production of text documents has seen an exponential growth, which is the reason why their proper classification seems necessary for better access. One of the main problems of classifying text documents is working in high-dimensional feature space. Feature Selection (FS) is one of the ways to reduce the number of text attributes. So, working with a great bulk of the feature spa...
متن کاملImage Retrieval Using Dynamic Weighting of Compressed High Level Features Framework with LER Matrix
In this article, a fabulous method for database retrieval is proposed. The multi-resolution modified wavelet transform for each of image is computed and the standard deviation and average are utilized as the textural features. Then, the proposed modified bit-based color histogram and edge detectors were utilized to define the high level features. A feedback-based dynamic weighting of shap...
متن کاملA Modified Grasshopper Optimization Algorithm Combined with CNN for Content Based Image Retrieval
Nowadays, with huge progress in digital imaging, new image processing methods are needed to manage digital images stored on disks. Image retrieval has been one of the most challengeable fields in digital image processing which means searching in a big database in order to represent similar images to the query image. Although many efficient researches have been performed for this topic so far, t...
متن کامل