The main objective of this study is to achieve sustainable regeneration strategies based on resilience dimensions in Karaj city. This research is a descriptive-analytical and applied research. Data collection has been done with library-documentary studies, surveys and interviews with city administrators and authorities, as well as for data analysis using the SWOTET technique, Vickor fuzzy and Topsis fuzzy were used. The results of the study indicate that the presence of suitable agricultural lands within the physical area of the city and its surroundings, the appropriate position on the Tehran-Qazvin highway and ongoing recreational design studies are among the opportunities available in the worn-out TEXTURE of the city of Karaj. Appropriate facilities for the implementation of councils at the whole neighborhood, lack of transparency in the implementation process of the plans prepared for the citizens and the low level of hygiene and lack of services are three major threats to the worn-out TEXTURE of Karaj. Based on the resilience dimension of Karaj City's worn-out tissue regeneration perspective, it has been formulated that the Karaj City's worn-out TEXTURE should be a coherent and secure structure with a sustainable and resilient urban infrastructure, facilities and equipment that has sustainable local communities. And be resilient to dynamic economic functions and operations to cope with any crisis. Studies based on strategies can also modify the structure of access to neighborhoods based on hierarchies to provide services in times of crisis and hazardousness, safety of urban facilities and equipment, retrofit of urban facilities and equipment, and detailed feasibility of resident participation. In line with the implementation of recreation and crisis management programs, identifying the responsibilities of urban managers based on comprehensive natural disaster management plans, creating an appropriate legal framework for public participation in recreation plans and programs to enhance resilience.

This article, an efficient system for TEXTURE defect detection based on curvelet transform is presented. The main idea is to model the defects in the TEXTURE image as one-dimensional discontinuities.Based on this idea, the curvelet transform is the most efficient method for describing defects. First, in the learning phase, training samples of intact and defected blocks of the TEXTURE image are collected and transformed to the curvelet domain. Next, for each block a feature vector based on curvelet sub-bands is extracted and using a proposed method some important and effective features are determined for the desired TEXTURE. Then, a proper threshold for detecting defected from intact blocks is determined. In the performance phase, a vector containing the important features from each block of the TEXTURE is extracted and then the block by is classified. The results of simulation show that the proposed system is superior to the mean shift method in detecting defected TEXTURE blocks, and is less sensitive to the type of TEXTURE.