So far, plant identification has challenges for several researchers. Various methods and features have been proposed. However, there are still many approaches could be investigated to develop robust plant identification systems. This paper reports several experiments in using Zernike moments to build foliage plant identification systems. In this case, Zernike moments were combined with other fe...

The level of quality in segmentation and classification tasks, operating on biomedical digital images, is strongly affected by the ability of the feature functions to map the input structures on “highly separated” data sets. This level of separation is strictly dependent by the “discriminatory power” of the chosen feature functions, meaning with this expression the property of the functions to ...

-This paper proposes a method for extracting GLCM Features on Local Directional Pattern based Fuzzy Co-occurrence matrix for effective face recognition. In this method Local Directional Pattern is computed on the image and then fuzzy representation is used for reduction of image edge responsiveness values. Contrast, correlation, energy and homogeneity features are evaluated over Co-occurrence m...

We introduce a simple image coding method, the block truncation coding (BTC) technique, as a novel approach to the construction of colour image databases. It is shown that BTC can not only be used to compress the images thus achieving storage eflciency. the BTC codes can also be used directly to construct image features for effective image retrieval. From the BTC code we have developed an image...

Orthoimages are aerial images where feature displacements and scale variations have been removed. This type of images is widely used to calculate areas, determine land cover and land use, among others. This paper introduces a rotation-invariant classification model for three common orthoimage regions: city, sea and forest areas, using only texture information (without color information). Our cl...

We present a new cooccurrence matrix based approach for multispectral texture analysis. The spectral and spatial domains of the multispectral textures are processed separately. The color space used in this study is represented by subspaces and it is class$ed by the averaged learning subspace method (ALSM). In the spatial domain we use a generalized cooccurrence matrix for vector valued pixels. ...

This paper presents a new application of a well-studied image coding technique, namely block truncation coding (BTC). It is shown that BTC can not only be used for compressing color images, it can also be conveniently used for content-based image retrieval from image databases. From the BTC compressed stream (without performing decoding), we derive two image content description features, one te...

This paper put forward a new method of co-occurrence matrix to describe image features. In this paper putting a new implemented work which is comparison with texton co-occurrence matrix to describe image features. Maximum work done successfully using texton co-occurrence matrix. A new class of texture features based on the co-occurrence of gray levels at points. These features are compared with...

Abstract: The pattern identification problems such as stone, rock categorization and wood recognition are used texture classification technique due to its valuable usage in it. Generally, texture analysis can be done one of the two ways i.e. statistical and structural approaches. More problems are occurred when working with statistical approaches in texture analysis for texture categorization. ...

The retrieval using single feature has a certain limitation, which fails to comprehensively describe an image. Aiming at such retrieval defect, this paper proposes an image retrieval method integrating color and texture. Firstly, carry out image segmentation with uniformly-spaced method, and then extract color feature of each segmentation with weighting processing done; and then, extract textur...