Feature Extraction and Image Retrieval of Landscape Images Based on Image Processing

Abstract

Facing the existing digital image libraries on landscape, researchers need to urgently solve a challenging problem: how to realize rational management and accurate retrieval of landscape images that contain feature information like hierarchy, layout, color system, and color matching. For accurate organization and labeling of landscape Images, this paper presents a novel method for feature extraction and image retrieval of landscape images based on image processing. Firstly, a color quantization process was designed for landscape images, and used to analyze the color composition and color space pattern (CSP) of such images. Next, the existing methods, which are suitable for the extraction of color features from landscape Images, were briefly reviewed, and the basic flows of our improved algorithm and division method of landscape color blocks (LCBs) were explained. Finally, the retrieval performance of landscape images was improved by matching of weighted color blocks of regional landscape, based on the multi-dimensional color eigenvectors of landscape image. The experimental results demonstrate the effectiveness of our algorithm. The research results shed light on the feature extraction from other types of color images.

[Retracted] Application of Neural Network Model Based on Multispecies Evolutionary Genetic Algorithm to Planning and Design of Diverse Plant Landscape

“…In order to reflect the overall unity and coordination of various landscape construction of landscape architecture, the relevant planning and design should fully combine the customs and geomorphology of the region, adopt the design method in accordance with local conditions, and carry out detailed planning and design on the basis of the local climate and geomorphology. To integrate plant landscape planning and design into landscape architecture, it is necessary to reflect the harmony between the two under the principle of overall unity, so as to provide a reference for the authenticity and feasibility of relevant design and planning [7][8][9]. When planning and designing the plant landscape of landscape architecture, we should use the strategy of conceptual planning, analyze the status quo of prebuilt landscape architecture through conceptual planning, set the planning and design goals of landscape architecture, combine these goals to do a good job in the multidimensional planning and design of landscape architecture, and design more details of landscape architecture accordingly.…”

Creating Color Image Features Based on Morphology Image Processing

“…Image features vector is an array of a fixed number of values, and this array can be used as an identifier or key to identify the image. To use the features vectors in the recognition system, the features vector must satisfy the following requirements [5][6][7][8][9][10][11][12][13][14]: • The method of calculating should be easy and effective, and it does not take much time to extract it. The stage of extracting the features of digital images and preserving these features is one of the important stages in building the discrimination system (see Figure 2) (extracted image features must be added to images features database, which will be used in a classification system, based for example on artificial neural network (ANN)), which in the future will affect its efficiency and the accuracy of reactions to this system [6,7].…”

Quantitative Morphology of Polder Landscape Based on SOM Identification Model: Case Study of Typical Polders in the South of Yangtze River

“…SEM [ 28 ] and hierarchical clustering [ 29 ] also provide practical tools for a comprehensive analysis of morphological data. Machine learning methods such as back propagation neural network [ 30 , 31 ] and convolutional neural network [ 32 ] can also achieve identification and classification of morphological unit types by learning morphological data [ 33 ]. On this basis, exploring data-driven landscape morphology research methods with the help of landscape morphology index and mathematical analysis model has positive significance for analyzing the feature of polder morphology.…”