The Weight Coefficient Of Woodimage Enhancement And Recognition Based On Frequency Domain

In the wood industry,the most commonly used method for identification of wood with visual observation,but the use of computer recognition more accurate.In the image acquisition process because of the environment and acquisition equipment factors,led to the image collected by the people is not ideal,so the extraction of texture information in wood loss,error this will lead to the identification of the image in the image of the wood.In this paper,the existing image enhancement algorithm based on image enhancement algorithm is proposed based on wood weight coefficient,analysis of the low frequency,high frequency and high performance wavelet transform high frequency band,so as to eliminate the confusion in the image,improve the image quality.The main contents of this paper include:1.This paper focuses on the histogram equalization algorithm,histogram algorithm,low-pass filtering algorithm,high pass filtering algorithm and wavelet transform algorithm,the five traditional image enhancement algorithm theory.2.In the existing image enhancement algorithm based on image enhancement algorithm is proposed based on the weight coefficient of wood,this is the main method of screening of directional image confusion in the backup,the whole image is divided into LL,LH,HL and HH four different bands of LL bands were normalized and the calculation method.The weight coefficient of similar modules,combined with the adaptive filtering module of LH,confusion detection;HL and HH were confused with local variance detection method.Finally the direction of its adaptive wavelet shrinkage to eliminate confusion,eliminate confusion complete image restoration through wavelet inverse transform.3.The algorithm and histogram equalization algorithm based on weight coefficient of reinforced wood image,histogram normalization algorithm,low-pass filtering,high pass filtering algorithm by experiments,and the subjective and objective analysis of the experimental results.4.The image enhancement algorithm is applied to the weight coefficient of wood image recognition based on the elm and elm bark as recognition samples respectively with wood image enhancement algorithm and the weight coefficient of the traditional image enhancement of elm wood and elm bark image preprocessing and image recognition based on BP neural network,and the the recognition results are analyzed and compared.