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Image processing has been widely used in criminal investigation. However, the robustness and real-time is contradictory for image processing of criminal investigation. To address the issue, we propose a new idea that images of criminal investigation are proceed by using deep learning networks. On the one hand, it is necessary to extract complex image features from the original image; on the other hand, deep learning is able to efficiently improve recognition ratio of objects. Based on these advantages, we propose the applications of deep learning in face recognition and pedestrian detection for criminal investigation. The simulation experiments show that the proposed method are able to quickly recognize face, and detect multi-pedestrian under complex environment, which is the basis of improving clear-up rate. Introduction Currently, public safety has become a key area for construction in all countries. However, monitoring and photographing can only obtain massive amounts data of images and video, but it lack of effective and intelligent algorithms to analysis so much data. How to effectively use the massive amount of data which obtained from different camera and photo tools every day is a major challenge for public safety [1] .At present ,The main issues of the image processing of criminal investigation can be divided into the following categories: image blurring problems, which are difficult to effectively recover blurred images due to the rapid movement of the target (such as a vehicle) and the inevitable wind .in addition, for the images got in smoggy weather, how to make the images clearly is a problem. For fast-distant shooting of face and license plates, how to quickly and accurately identify is a problem. For multiple pedestrian targets in a complex environment, the problem that how to correctly detect and identify also needs to be resolved. There are a large number of image and video processing algorithms applied in industry and life, but it is difficult to get great results in criminal investigation image applications. Because the environment has a large impact for that. for example, Although the current face recognition algorithm can achieve a recognition rate of 99.9% in an ordinary indoor, the face recognition of criminal investigation is less than 50%. Deep Learning Deep Learning [2-3] originates from the research of artificial neural networks and is a new field in machine learning research. Data is abstracted at a high level by using complex structures or the multiple processing layers of multiple nonlinear transformations. It forms a more abstract high-level to represent attribute or feature by combining low-level features to discover the data’s representation in distributed feature. It is a method of Characteristic learning based on data. There are so many cities in China have deployed a large number of cameras and capture probes. There are so much data obtained by the Police system every day. How to effectively use these data and extract useful information from them to improve the efficiency of detection is a problem. With the rapid development of deep learning, solving this problem becomes possible. Because deep learning relies on massive data of sample, and the Police system exactly meets this condition, so the use of deep learning to improve the image processing quality and effectively identify the target is a

Deep Learning-based New Methods of Images Processing for Criminal Investigation