Image recognition based on Boltzmann machine algorithm

Due to the influence of recognition parameters, image recognition has low recognition accuracy, long recognition time and large storage cost. Therefore, an automatic image recognition method based on Boltzmann machine is proposed. Based on threshold method and fuzzy set method, image malformation correction is performed. The mean filter and median filter are combined to eliminate the influence of image filtering, and the pre-processing of image is completed by using the fuzzy enhancement of image. Based on the restricted Boltzmann method, the network model is dynamically evolved, and the identification parameters of each shape and contour are obtained. Different shapes and contours are classified and recognized. Simulation results show that image recognition method based on human-computer interaction has high recognition ability, shortens the time cost and greatly reduces the space needed for node storage.

Design and Analysis Of Underwater Imaging Application susing High Frequency Array

Underwater picture preparing has a few applications in the field of maritime exploration work and logical applications, for example, archaeology, geography, underwater ecological appraisal, laying of significant distance gas pipelines and correspondence joins across the mainlands which request geo-referential looking over of the maritime bed and prospection of complex task. The lowering of a camera underwater requires satisfactory lodging utilizing high frequency. The moving of the camera with the assistance from distant spot or face to face at the site is similarly a perplexing undertaking. In any case, the significant test is forced by underwater medium properties. Underwater dimness picture upgrade has acquired far and wide significance with the quick advancement of present day imaging gear. Notwithstanding, the difference upgrade of single underwater dim picture is a difficult errand for logical investigation and computational applications. Versatile differentiation upgrade calculations to determine the picture fluffiness was proposed to suit underwater pictures with shifting difference. Fuzzy edge held intensification strategy had the option to furnish better upgrade with very much protected edge data and improved differentiation in examination with the fuzzy enhancement technique. Acoustic imaging systems are likewise valuable for reviewing or inspecting objects when water turbidity blocks the utilization of closed circuit television or other optical methods for survey. Likewise, light is weakened with a horizontal distance of proliferation, decreasing the light energy arriving at the camera, accordingly bringing about a deficiency of the normal tone.

Degraded Image Enhancement Using Dual-Domain-Adaptive Wavelet and Improved Fuzzy Transform

A novel enhancement algorithm for degraded image using dual-domain-adaptive wavelet and improved fuzzy transform is proposed, aiming at the problem of surveillance videos degradation caused by the complex lighting conditions underground coal mine. Firstly, the dual-domain filtering (DDF) is used to decompose the image into base image and detail image, and the contrast limited adaptive histogram enhancement (CLAHE) is adopted to adjust the overall brightness and contrast of the base image. Then, the discrete wavelet transform (DWT) is utilized to obtain the low frequency sub-band (LFS) and high frequency sub-band (HFS). Next, the wavelet shrinkage threshold is applied to calculate the wavelet threshold corresponding to the HFS at different scales. Meanwhile, a new Garrate threshold function that introduces adjustment factor and enhancement coefficient is designed to adaptively de-noise and enhance the HFS coefficients, and the Gamma function is employed to correct the LFS coefficients. Finally, the PAL fuzzy enhancement operator is improved and used to perform contrast enhancement and highlight area suppression on the reconstructed image to obtain an enhanced image. Experimental results show that the proposed algorithm can not only significantly improve the overall brightness and contrast of the degraded image but also suppresses the noise of dust and spray and enhances the image details. Compared with the similar algorithms of STFE, GTFE, CLAHE, SSR, MSR, DGR, and MSWT algorithms, the indicator values of comprehensive performance of the proposed algorithm are increased by 205%, 195%, 200%, 185%, 185%, 85%, 140%, and 215%, respectively. Moreover, compared with the other seven algorithms, the proposed algorithm has strong robustness and is more suitable for image enhancement in different mine environments.