A privacy-preserving image retrieval method based on deep learning and adaptive weighted fusion

Polar harmonic transforms (PHTs) have been applied in pattern recognition and image analysis. But the current computational framework of PHTs has two main demerits. First, some significant color information may be lost during color image processing in conventional methods because they are based on RGB decomposition or graying. Second, PHTs are influenced by geometric errors and numerical integration errors, which can be seen from image reconstruction errors. This paper presents a novel computational framework of quaternion polar harmonic transforms (QPHTs), namely, accurate QPHTs (AQPHTs). First, to holistically handle color images, quaternion-based PHTs are introduced by using the algebra of quaternions. Second, the Gaussian numerical integration is adopted for geometric and numerical error reduction. When compared with CNNs (convolutional neural networks)-based methods (i.e., VGG16) on the Oxford5K dataset, our AQPHT achieves better performance of scaling invariant representation. Moreover, when evaluated on standard image retrieval benchmarks, our AQPHT using smaller dimension of feature vector achieves comparable results with CNNs-based methods and outperforms the hand craft-based methods by 9.6% w.r.t mAP on the Holidays dataset.

Section: Experiments On Image Retrievalmentioning

confidence: 90%

Section: Experiments On Image Retrievalmentioning

confidence: 99%

Accurate Quaternion Polar Harmonic Transform for Color Image Analysis

Zhang¹,

Sang

Dai³

2021

“…And mark the start point and end point, respectively, and record their coordinates. When scanning to the starting point, it will follow the direction of the starting point adjacent to the target pixel to the target end, and at the same time record the direction number of the current pixel relative to the previous pixel, and finally complete the chain coding of a curve [29,30].…”

Section: Image Chain Coding Processing After the Art Visionmentioning

confidence: 99%

The Stereo Communication Method of Artistic Visual Image Based on CAD Platform

Gao

Wang

2022

Due to the large amount of noise in the image background, the traditional methods have the problems of poor image communication effect, slow image communication efficiency, and poor noise processing effect. A three-dimensional communication method of art visual image based on CAD platform is proposed. Wavelet transform is used to extract artistic visual image features, and the fuzzy clustering method is used to standardize the obtained image feature data. Based on the data processing results, the CAD platform is constructed, the software program is designed, and the image chain coding is realized at the same time. The particle swarm optimization algorithm is used to convey the image of the obtained CAD general vectorization file, so as to complete the three-dimensional transmission of artistic visual image. The experimental results show that the image communication effect of this method is better, the image communication efficiency is higher, the noise suppression effect is better, the visual communication effect of the image is improved, and the performance of the designed method is superior.

“…(3) Configuration platform: in order to facilitate the calling of artistic visual image scene during rendering, preprocess each scene (4) Display rendering results: obtain the state parameters generated by the platform itself and external input and control and display the objects in the scene, so as to optimize the display of artistic visual images and complete the visual communication design [34][35][36]…”

Section: Visual Effect Renderingmentioning

confidence: 99%

Art Visual Image Transmission Method Based on Cartesian Genetic Programming

Zhao

2021

Because most of the traditional artistic visual image communication methods use the form of modeling and calculation, there are some problems such as long image processing time, low success rate of image visual communication, and poor visual effect. An artistic visual image communication method based on Cartesian genetic programming is proposed. The visual expression sensitivity difference method is introduced to process the image data, the neural network is used to identify the characteristics of the artistic visual image, the midpoint displacement method is used to remove the folds of the artistic visual image, and the processed image is formed under the above three links. The Cartesian genetic programming algorithm is used to encode the preprocessed image, improve the fitness function, select the algorithm to improve the operation, design the image rendering platform, input the processed image to the platform, and complete the artistic visual image transmission. The analysis of the experimental results shows that the image processing time of this method is short, the success rate of visual communication is high, and the image visual effect is good, which can obtain the image processing results satisfactory to users.