Research On Content Based On Image Retrieval And Motion Detection On The Video

The purpose of image understanding lies in intelligentizing image information processing, moreover it can replace parts of human work. Image understanding is a kind of description or certain sort concerning image contents, its description or sort is completed and evaluated by the computer instead of human vision. The object of computer vision research is to make meaningful judgment on practical objects and scenes according to image construction scene and acquired images, comprehend and describe its behavior and realize"vision intelligence"The research of this paper is based on the leading projects"Identity authentication system based on biologic feature recognition"and"Key science and technology development plan project of Jilin province"of the national 863 plan, and is applied in the image retrieval and motion object detection of network intelligent camera. By performing motion detection to the images in video stream and retrieval based on content on sensitive information, we can make judgment to the given images, such as, identify"human"activities in surveillant scene, detect"fire"alarm information in the forest fire monitoring situation etc. This paper focuses on the vision information of images and discusses the problems of retrieval based on content and object detection.Color feature is not neglectable in the process of image retrieval because it's very straight forward. This paper focuses on the color distribution feature of image, and puts forward to extract color feature of different sub blocks and regions respectively by sub block partition to the image and reasonable region, and introduces an algorithm that makes use of DCT and SVD to extract color feature and reduce dimension. The experiment proves that the method has achieved a better complete check rate and accuracy check rate, having preferable retrieval effect. At the same time we analyze the limitation of color feature and discuss method that combines texture, shape and fractal, trying to achieve better retrieval effect. In order to fully express the self resemblance color feature of the images, this paper puts forward the self resemblance feature coding method, which expands the code space from the gradation dimension to chromatic dimension. At the same time, central diffusion algorithm which can effectively shorten computing time, enhance the feasibility of the algorithm while ensuring certain degree of matching error is adopted because of the great computation quantity, low speed problems of the traditional fractal encoding. Finally, image retrieval can be implemented by extracting feature vector from the self resemblance feature coding using singularity value decomposition. The experimental result shows that this algorithm has better real-time quality.The given image compression algorithm makes use of lifting wavelet transformation and self-adapting binary arithmetic coding method, and presents the dynamic variety diploid method which solves the network bandwidth problem preferably.At last this paper introduces an embedded system engineering design idea and designs the hardware architecture of network camera based on it. We discuss the key problems in the embedded hardware implementation-parallelism of algorithm, data reusing, and system security. We resolve the huge amount of information and limited bandwidth resource problems that as merely an input end, the traditional network camera will send the image information captured directly to the server without any processing 24 hours ceaselessly. At the same time, this paper presents a retrieval method that can detect accidents and security hidden trouble immediately from massive information. Security monitoring has experienced three generations of development, the first generation is simulated image monitoring, the second is monitoring based on PC technology, the third is network digital monitoring. The"network camera based on image retrieval"which has"vision intelligence"and based on the research achievement of this paper belongs to the new generation network monitoring machine."Image content retrieval and motion object detection of video stream"is a problem that involves multiple subjects. The research of image retrieval and motion object detection have obtained some achievement, but compared to human perception ability, there is still a large gap between them. The successive research of this paper will try to apply semantic technique in the compile technology in the research of image understanding and plan to solve the difficulty of how to extract semantic feature from images and describe it. Searching and developing new technology can help to improve image target identification and understanding, it also can reduce the computing complexity effectively.