Colour, Texture, and Shape Features based Object Recognition Using Distance Measures

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S.M. Mohidul Islam 1,* Farhana Tazmim Pinki 1

1. Computer Science and Engineering Discipline, Khulna University, Khulna, Bangladesh

* Corresponding author.


Received: 22 Jun. 2021 / Revised: 2 Jul. 2021 / Accepted: 25 Jul. 2021 / Published: 8 Aug. 2021

Index Terms

Color Histogram, Gabor Wavelet, Hough Transform, Nearest Neighbor, Ensemble of Distance Measures.


Object recognition is the recognizing process of objects into semantically expressive classes using its visual insides. Classification of objects becomes complex and challenging task because of its size, poor image quality, occlusion, scaling, geometric distortion, lightening, etc. In this paper, global descriptors that means Color, Texture, and Shape features are used to recognize object. Color histogram is used to obtain the color content, texture content is obtained using Gabor wavelet, and shape content is extracted using Hough transform. These low level or global features are used for creating feature vector. Distance measure is used to find the 1-Nearest Neighbor from the training images i.e. object with minimum distance or maximum similarity with visual contents of the query image. The class of that training image is the predicted label of the query image. We have used twelve different distance measures: some are metrics, some are non-metrics and finally, their recognition accuracy is compared. Ensemble of these distance measures is also used for object recognition in the image. We evaluate this method on a publicly available object-recognition dataset: Columbia Object Image Library (COIL-100) dataset. The experiments show that the recognized results outperform many state-of-the-art methods.

Cite This Paper

S.M. Mohidul Islam, Farhana Tazmim Pinki, " Colour, Texture, and Shape Features based Object Recognition Using Distance Measures", International Journal of Engineering and Manufacturing (IJEM), Vol.11, No.4, pp. 42-50, 2021. DOI: 10.5815/ijem.2021.04.05


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