When using image processing technology to analyze mineral particle size in complex scenes, it is difficult to separate the objects from the background with traditional algorithms. This paper proposes an ore image segmentation algorithm based on a histogram accumulation moment, which is applied to multi-scenario ore object location and recognition. Firstly, the multi-scale Retinex color restoration algorithm is used to improve the contrast in the dark region and eliminates the shadows generated by the stacked adhesion ores. Then, the zero-order and first-order cumulative moments close to the selected gray level are calculated, reducing the error caused by noise. Finally, the selected gray level gradually approaches the optimal threshold to avoid falling into local optimum. It can segment mineral images with unimodal or insignificant bimodal characteristic histogram effectively and accurately. Ore images in three different scenarios are used to verify the accuracy and effectiveness of the proposed method. The experimental results demonstrate that the proposed algorithm provides better segmentation results than other methods.

Watermarking is an effective solution for copyright protection and forensics tracking via hiding information into the image signal. Recently, spatial-embedding watermarking methods from different transform domain have been proposed rapidly and effectively protect the copyright of the color image. Compared to the individual frequency domain method, it has both advantages of spatial domain and frequency domain. Here, we proposed a novel spatial-embedding watermarking method based on an attended just noticeable difference (JND) model with color complexity, to achieve a good tradeoff between robustness and perceptual quality. In particular, at the spatial embedding level, the direct current (DC) coefficients are selected for embedding and the perceptual JND model is used to guide the amount of pixel modification to improve visual quality. Different from the previous JND model, we proposed an attended JND model that considers color complexity, which is more consistent of the human visual perception model. Compared with the other JND models, the proposed JND model is more suitable for the watermarking framework. Experimental results show that the proposed watermarking scheme has better performance than other existing watermarking schemes. This greatly benefits the practical implementations of the spatialembedding watermarking methods.

A novel block-level perceptual image watermarking framework is proposed in this study, including tridirectional correlation and a block-level just noticeable difference (JND) model. Specifically, the difference in the discrete cosine transform (DCT) coefficients of two blocks is calculated based on three directions in the neighborhood, called the tri-directional correlation (TriDC). Additionally, the representative alternating current (AC) coefficients along horizontal, vertical, and diagonal directions, which can describe structural patterns, are projected and merged for TriDC differences. Then, the difference of the DCT coefficient is modulated to a predefined zone depending on the JNDbased offset. Finally, the extent of the watermarked AC coefficients is determined with perceptual JND adjustment. The experimental results demonstrate that the proposed scheme can protect most common image processing attacks; and has better robustness compared with recent zone modulation watermarking schemes and traditional watermarking methods.image watermarking, JND model, robustness, spread transform, tri-directional With the rapid development of digital technologies within the past few decades, digital images are more convenient for transmission, duplication, and modification, which means the ease of several urgent issues relating to copyright protection and authentication. It is increasingly important to be able to improve image security and protection against illegal actions and possible violations during distribution over communications links; and computer networks. [1][2][3][4][5][6] Digital watermarking is a robust and maintainable solution for data hiding, whereby the watermark is embedded into the host image, and extracted to identify ownership.In this paper, we focus on image watermarking. Image watermarking can be effective only if the watermarked image has minimum distortion, and the watermark can be extracted with maximum robustness. Unfortunately, there exists a contradiction between the image fidelity and robustness for the image watermarking method. Generally, increasing the robustness occurs at the cost of hampering the quality and utility of the image, and vice versa. They are mutually constrained. Consequently, a better tradeoff between fidelity and robustness is required for a well-designed watermarking algorithm.Currently, the common embedding schemes fall into two categories, namely spatial and transformed domain schemes. Both of them have their inherent characteristics. The former has lower computational complexity but poor robustness. The latter can significantly improve robustness while ensuring image quality. They also have an acquired deficiency, using equal embedding strength for different regions in the image, which intensifies the contradiction between the robustness and fidelity. The discrete cosine transform (DCT), most popular in the transform domain, has been applied for software and hardware implementations in low-cost devices.This paper addresses these issues by studying the correlation betwe...

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